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Daniel Cremers
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- affiliation: Technical University Munich, Germany
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2020 – today
- 2024
- [j93]Dekai Zhu, Qadeer Khan, Daniel Cremers:
Multi-vehicle trajectory prediction and control at intersections using state and intention information. Neurocomputing 574: 127220 (2024) - [c374]Adrian Hayler, Felix Wimbauer, Dominik Muhle, Christian Rupprecht, Daniel Cremers:
S4C: Self-Supervised Semantic Scene Completion With Neural Fields. 3DV 2024: 409-420 - [c373]Simon Klenk, Marvin Motzet, Lukas Koestler, Daniel Cremers:
Deep Event Visual Odometry. 3DV 2024: 739-749 - [c372]Viktoria Ehm, Paul Roetzer, Marvin Eisenberger, Maolin Gao, Florian Bernard, Daniel Cremers:
Geometrically Consistent Partial Shape Matching. 3DV 2024: 914-922 - [c371]Christian Tomani, David Vilar, Markus Freitag, Colin Cherry, Subhajit Naskar, Mara Finkelstein, Xavier Garcia, Daniel Cremers:
Quality-Aware Translation Models: Efficient Generation and Quality Estimation in a Single Model. ACL (1) 2024: 15660-15679 - [c370]Zhenzhang Ye, Gabriel Peyré, Daniel Cremers, Pierre Ablin:
Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization. AISTATS 2024: 955-963 - [c369]Moritz Zaiss, Junaid R. Rajput, Hoai Nam Dang, Vladimir Golkov, Daniel Cremers, Florian Knoll, Andreas K. Maier:
Exploring GPT-4 as MR Sequence and Reconstruction Programming Assistant - GPT4MR. Bildverarbeitung für die Medizin 2024: 94-99 - [c368]Simon Weber, Thomas Dagès, Maolin Gao, Daniel Cremers:
Finsler-Laplace-Beltrami Operators with Application to Shape Analysis. CVPR 2024: 3131-3140 - [c367]Dongliang Cao, Marvin Eisenberger, Nafie El Amrani, Daniel Cremers, Florian Bernard:
Spectral Meets Spatial: Harmonising 3D Shape Matching and Interpolation. CVPR 2024: 3658-3668 - [c366]Christoph Reich, Oliver Hahn, Daniel Cremers, Stefan Roth, Biplob Debnath:
A Perspective on Deep Vision Performance with Standard Image and Video Codecs. CVPR Workshops 2024: 5712-5721 - [c365]Christoph Reich, Biplob Debnath, Deep Patel, Tim Prangemeier, Daniel Cremers, Srimat Chakradhar:
Deep Video Codec Control for Vision Models. CVPR Workshops 2024: 5732-5741 - [c364]Felix Wimbauer, Bichen Wu, Edgar Schönfeld, Xiaoliang Dai, Ji Hou, Zijian He, Artsiom Sanakoyeu, Peizhao Zhang, Sam S. Tsai, Jonas Kohler, Christian Rupprecht, Daniel Cremers, Peter Vajda, Jialiang Wang:
Cache Me if You Can: Accelerating Diffusion Models through Block Caching. CVPR 2024: 6211-6220 - [c363]Keonhee Han, Dominik Muhle, Felix Wimbauer, Daniel Cremers:
Boosting Self-Supervision for Single-View Scene Completion via Knowledge Distillation. CVPR 2024: 9837-9847 - [c362]Mohammed Brahimi, Bjoern Haefner, Zhenzhang Ye, Bastian Goldluecke, Daniel Cremers:
Sparse Views, Near Light: A Practical Paradigm for Uncalibrated Point-Light Photometric Stereo. CVPR 2024: 11862-11872 - [c361]Yan Xia, Letian Shi, Zifeng Ding, João F. Henriques, Daniel Cremers:
Text2Loc: 3D Point Cloud Localization from Natural Language. CVPR 2024: 14958-14967 - [c360]Viktoria Ehm, Maolin Gao, Paul Roetzer, Marvin Eisenberger, Daniel Cremers, Florian Bernard:
Partial-to-Partial Shape Matching with Geometric Consistency. CVPR 2024: 27478-27487 - [c359]Aysim Toker, Marvin Eisenberger, Daniel Cremers, Laura Leal-Taixé:
SatSynth: Augmenting Image-Mask Pairs Through Diffusion Models for Aerial Semantic Segmentation. CVPR 2024: 27685-27695 - [c358]Simon Weber, Baris Zöngür, Nikita Araslanov, Daniel Cremers:
Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincaré Ball. CVPR 2024: 28223-28232 - [c357]Simon Weber, Je Hyeong Hong, Daniel Cremers:
Power Variable Projection for Initialization-Free Large-Scale Bundle Adjustment. ECCV (13) 2024: 111-126 - [c356]Mihir Mahajan, Florian Hofherr, Daniel Cremers:
MeshFeat: Multi-resolution Features for Neural Fields on Meshes. ECCV (29) 2024: 268-285 - [c355]Linyan Yang, Lukas Hoyer, Mark Weber, Tobias Fischer, Dengxin Dai, Laura Leal-Taixé, Marc Pollefeys, Daniel Cremers, Luc Van Gool:
MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation. ECCV (39) 2024: 329-346 - [c354]Bangyan Liao, Zhenjun Zhao, Lu Chen, Haoang Li, Daniel Cremers, Peidong Liu:
GlobalPointer: Large-Scale Plane Adjustment with Bi-Convex Relaxation. ECCV (59) 2024: 360-376 - [c353]Linus Härenstam-Nielsen, Lu Sang, Abhishek Saroha, Nikita Araslanov, Daniel Cremers:
DiffCD: A Symmetric Differentiable Chamfer Distance for Neural Implicit Surface Fitting. ECCV (73) 2024: 432-447 - [c352]Christian Koke, Daniel Cremers:
HoloNets: Spectral Convolutions do extend to Directed Graphs. ICLR 2024 - [c351]Sergei Solonets, Daniil Sinitsyn, Lukas von Stumberg, Nikita Araslanov, Daniel Cremers:
An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment. ICLR 2024 - [c350]Yuesong Shen, Nico Daheim, Bai Cong, Peter Nickl, Gian Maria Marconi, Clement Bazan, Rio Yokota, Iryna Gurevych, Daniel Cremers, Mohammad Emtiyaz Khan, Thomas Möllenhoff:
Variational Learning is Effective for Large Deep Networks. ICML 2024 - [c349]Dominik Rößle, Jeremias Gerner, Klaus Bogenberger, Daniel Cremers, Stefanie Schmidtner, Torsten Schön:
Unlocking Past Information: Temporal Embeddings in Cooperative Bird's Eye View Prediction. IV 2024: 2220-2225 - [c348]Simon Klenk, David Bonello, Lukas Koestler, Nikita Araslanov, Daniel Cremers:
Masked Event Modeling: Self-Supervised Pretraining for Event Cameras. WACV 2024: 2367-2377 - [c347]Tarun Yenamandra, Ayush Tewari, Nan Yang, Florian Bernard, Christian Theobalt, Daniel Cremers:
FIRe: Fast Inverse Rendering using Directional and Signed Distance Functions. WACV 2024: 3065-3075 - [c346]Mohammed Brahimi, Bjoern Haefner, Tarun Yenamandra, Bastian Goldluecke, Daniel Cremers:
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering. WACV 2024: 3127-3137 - [c345]Ugur Sahin, Hang Li, Qadeer Khan, Daniel Cremers, Volker Tresp:
Enhancing Multimodal Compositional Reasoning of Visual Language Models with Generative Negative Mining. WACV 2024: 5551-5561 - [i234]Dominik Rößle, Jeremias Gerner, Klaus Bogenberger, Daniel Cremers, Stefanie Schmidtner, Torsten Schön:
Unlocking Past Information: Temporal Embeddings in Cooperative Bird's Eye View Prediction. CoRR abs/2401.14325 (2024) - [i233]Zhenzhang Ye, Gabriel Peyré, Daniel Cremers, Pierre Ablin:
Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization. CoRR abs/2402.16748 (2024) - [i232]Yuesong Shen, Nico Daheim, Bai Cong, Peter Nickl, Gian Maria Marconi, Clement Bazan, Rio Yokota, Iryna Gurevych, Daniel Cremers, Mohammad Emtiyaz Khan, Thomas Möllenhoff:
Variational Learning is Effective for Large Deep Networks. CoRR abs/2402.17641 (2024) - [i231]Dongliang Cao, Marvin Eisenberger, Nafie El Amrani, Daniel Cremers, Florian Bernard:
Spectral Meets Spatial: Harmonising 3D Shape Matching and Interpolation. CoRR abs/2402.18920 (2024) - [i230]Abhishek Saroha, Mariia Gladkova, Cecilia Curreli, Tarun Yenamandra, Daniel Cremers:
Gaussian Splatting in Style. CoRR abs/2403.08498 (2024) - [i229]Yun-Jin Li, Mariia Gladkova, Yan Xia, Rui Wang, Daniel Cremers:
VXP: Voxel-Cross-Pixel Large-scale Image-LiDAR Place Recognition. CoRR abs/2403.14594 (2024) - [i228]Aysim Toker, Marvin Eisenberger, Daniel Cremers, Laura Leal-Taixé:
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation. CoRR abs/2403.16605 (2024) - [i227]Mohammed Brahimi, Bjoern Haefner, Zhenzhang Ye, Bastian Goldluecke, Daniel Cremers:
Sparse Views, Near Light: A Practical Paradigm for Uncalibrated Point-light Photometric Stereo. CoRR abs/2404.00098 (2024) - [i226]Simon Weber, Baris Zöngür, Nikita Araslanov, Daniel Cremers:
Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincar\'e Ball. CoRR abs/2404.03778 (2024) - [i225]Simon Weber, Thomas Dagès, Maolin Gao, Daniel Cremers:
Finsler-Laplace-Beltrami Operators with Application to Shape Analysis. CoRR abs/2404.03999 (2024) - [i224]Keonhee Han, Dominik Muhle, Felix Wimbauer, Daniel Cremers:
Boosting Self-Supervision for Single-View Scene Completion via Knowledge Distillation. CoRR abs/2404.07933 (2024) - [i223]Christian Tomani, Kamalika Chaudhuri, Ivan Evtimov, Daniel Cremers, Mark Ibrahim:
Uncertainty-Based Abstention in LLMs Improves Safety and Reduces Hallucinations. CoRR abs/2404.10960 (2024) - [i222]Viktoria Ehm, Maolin Gao, Paul Roetzer, Marvin Eisenberger, Daniel Cremers, Florian Bernard:
Partial-to-Partial Shape Matching with Geometric Consistency. CoRR abs/2404.12209 (2024) - [i221]Christoph Reich, Oliver Hahn, Daniel Cremers, Stefan Roth, Biplob Debnath:
A Perspective on Deep Vision Performance with Standard Image and Video Codecs. CoRR abs/2404.12330 (2024) - [i220]Simon Weber, Je Hyeong Hong, Daniel Cremers:
Power Variable Projection for Initialization-Free Large-Scale Bundle Adjustment. CoRR abs/2405.05079 (2024) - [i219]Qihang Yu, Mark Weber, Xueqing Deng, Xiaohui Shen, Daniel Cremers, Liang-Chieh Chen:
An Image is Worth 32 Tokens for Reconstruction and Generation. CoRR abs/2406.07550 (2024) - [i218]Gengyuan Zhang, Mang Ling Ada Fok, Yan Xia, Yansong Tang, Daniel Cremers, Philip Torr, Volker Tresp, Jindong Gu:
Localizing Events in Videos with Multimodal Queries. CoRR abs/2406.10079 (2024) - [i217]Yan Xia, Ran Ding, Ziyuan Qin, Guanqi Zhan, Kaichen Zhou, Long Yang, Hao Dong, Daniel Cremers:
TARGO: Benchmarking Target-driven Object Grasping under Occlusions. CoRR abs/2407.06168 (2024) - [i216]Bangyan Liao, Zhenjun Zhao, Lu Chen, Haoang Li, Daniel Cremers, Peidong Liu:
GlobalPointer: Large-Scale Plane Adjustment with Bi-Convex Relaxation. CoRR abs/2407.13537 (2024) - [i215]Mihir Mahajan, Florian Hofherr, Daniel Cremers:
MeshFeat: Multi-Resolution Features for Neural Fields on Meshes. CoRR abs/2407.13592 (2024) - [i214]Linus Härenstam-Nielsen, Lu Sang, Abhishek Saroha, Nikita Araslanov, Daniel Cremers:
DiffCD: A Symmetric Differentiable Chamfer Distance for Neural Implicit Surface Fitting. CoRR abs/2407.17058 (2024) - [i213]Fabian Bongratz, Vladimir Golkov, Lukas Mautner, Luca Della Libera, Frederik Heetmeyer, Felix Czaja, Julian Rodemann, Daniel Cremers:
How to Choose a Reinforcement-Learning Algorithm. CoRR abs/2407.20917 (2024) - [i212]Aymeric Fleith, Doaa Ahmed, Daniel Cremers, Niclas Zeller:
LiFCal: Online Light Field Camera Calibration via Bundle Adjustment. CoRR abs/2408.11682 (2024) - [i211]Johannes Meier, Luca Scalerandi, Oussema Dhaouadi, Jacques Kaiser, Nikita Araslanov, Daniel Cremers:
CARLA Drone: Monocular 3D Object Detection from a Different Perspective. CoRR abs/2408.11958 (2024) - [i210]Tianfei Zhou, Fei Zhang, Boyu Chang, Wenguan Wang, Ye Yuan, Ender Konukoglu, Daniel Cremers:
Image Segmentation in Foundation Model Era: A Survey. CoRR abs/2408.12957 (2024) - [i209]Linyan Yang, Lukas Hoyer, Mark Weber, Tobias Fischer, Dengxin Dai, Laura Leal-Taixé, Marc Pollefeys, Daniel Cremers, Luc Van Gool:
MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation. CoRR abs/2408.16478 (2024) - [i208]Yining Ma, Ang Li, Qadeer Khan, Daniel Cremers:
Enhancing the Performance of Multi-Vehicle Navigation in Unstructured Environments using Hard Sample Mining. CoRR abs/2409.05119 (2024) - [i207]Lei Cheng, Junpeng Hu, Haodong Yan, Mariia Gladkova, Tianyu Huang, Yun-Hui Liu, Daniel Cremers, Haoang Li:
Physically-Based Photometric Bundle Adjustment in Non-Lambertian Environments. CoRR abs/2409.11854 (2024) - [i206]Mark Weber, Lijun Yu, Qihang Yu, Xueqing Deng, Xiaohui Shen, Daniel Cremers, Liang-Chieh Chen:
MaskBit: Embedding-free Image Generation via Bit Tokens. CoRR abs/2409.16211 (2024) - 2023
- [j92]Qadeer Khan, Idil Sülö, Melis Öcal, Daniel Cremers:
Learning vision based autonomous lateral vehicle control without supervision. Appl. Intell. 53(16): 19186-19198 (2023) - [j91]Zhenzhang Ye, Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff, Daniel Cremers:
A Cutting-Plane Method for Sublabel-Accurate Relaxation of Problems with Product Label Spaces. Int. J. Comput. Vis. 131(1): 346-362 (2023) - [j90]Simon Klenk, Lukas Koestler, Davide Scaramuzza, Daniel Cremers:
E-NeRF: Neural Radiance Fields From a Moving Event Camera. IEEE Robotics Autom. Lett. 8(3): 1587-1594 (2023) - [j89]Jiaxin Pan, Changyao Zhou, Mariia Gladkova, Qadeer Khan, Daniel Cremers:
Robust Autonomous Vehicle Pursuit Without Expert Steering Labels. IEEE Robotics Autom. Lett. 8(10): 6595-6602 (2023) - [j88]Sherwin Bahmani, Oliver Hahn, Eduard Zamfir, Nikita Araslanov, Daniel Cremers, Stefan Roth:
Semantic Self-adaptation: Enhancing Generalization with a Single Sample. Trans. Mach. Learn. Res. 2023 (2023) - [c344]Simon Weber, Nikolaus Demmel, Tin Chon Chan, Daniel Cremers:
Power Bundle Adjustment for Large-Scale 3D Reconstruction. CVPR 2023: 281-289 - [c343]Linus Härenstam-Nielsen, Niclas Zeller, Daniel Cremers:
Semidefinite Relaxations for Robust Multiview Triangulation. CVPR 2023: 749-757 - [c342]Olaf Wysocki, Yan Xia, Magdalena Wysocki, Eleonora Grilli, Ludwig Hoegner, Daniel Cremers, Uwe Stilla:
Scan2LoD3: Reconstructing semantic 3D building models at LoD3 using ray casting and Bayesian networks. CVPR Workshops 2023: 6548-6558 - [c341]Felix Wimbauer, Nan Yang, Christian Rupprecht, Daniel Cremers:
Behind the Scenes: Density Fields for Single View Reconstruction. CVPR 2023: 9076-9086 - [c340]Dominik Muhle, Lukas Koestler, Krishna Murthy Jatavallabhula, Daniel Cremers:
Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares. CVPR 2023: 13102-13112 - [c339]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
G-MSM: Unsupervised Multi-Shape Matching with Graph-Based Affinity Priors. CVPR 2023: 22762-22772 - [c338]Viktoria Ehm, Daniel Cremers, Florian Bernard:
Non-Separable Multi-Dimensional Network Flows for Visual Computing. Eurographics (Posters) 2023: 15-16 - [c337]Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Möller, Daniel Cremers, Florian Bernard:
ΣIGMA: Scale-Invariant Global Sparse Shape Matching. ICCV 2023: 645-654 - [c336]Yan Xia, Mariia Gladkova, Rui Wang, Qianyun Li, Uwe Stilla, João F. Henriques, Daniel Cremers:
CASSPR: Cross Attention Single Scan Place Recognition. ICCV 2023: 8427-8438 - [c335]Marc Botet Colomer, Pier Luigi Dovesi, Theodoros Panagiotakopoulos, Joao Frederico Carvalho, Linus Härenstam-Nielsen, Hossein Azizpour, Hedvig Kjellström, Daniel Cremers, Matteo Poggi:
To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation. ICCV 2023: 16502-16513 - [c334]Haoang Li, Jinhu Dong, Binghui Wen, Ming Gao, Tianyu Huang, Yun-Hui Liu, Daniel Cremers:
DDIT: Semantic Scene Completion via Deformable Deep Implicit Templates. ICCV 2023: 21837-21847 - [c333]Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel:
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks. ICML 2023: 30252-30284 - [c332]Christian Tomani, Futa Kai Waseda, Yuesong Shen, Daniel Cremers:
Beyond In-Domain Scenarios: Robust Density-Aware Calibration. ICML 2023: 34344-34368 - [c331]Jeremias Gerner, Dominik Rößle, Daniel Cremers, Klaus Bogenberger, Torsten Schön, Stefanie Schmidtner:
Enhancing Realistic Floating Car Observers in Microscopic Traffic Simulation. ITSC 2023: 2396-2403 - [c330]Jonathan Schmidt, Qadeer Khan, Daniel Cremers:
LiDAR View Synthesis for Robust Vehicle Navigation Without Expert Labels. ITSC 2023: 2835-2842 - [c329]Yining Ma, Qadeer Khan, Daniel Cremers:
Multi Agent Navigation in Unconstrained Environments using a Centralized Attention based Graphical Neural Network Controller. ITSC 2023: 2893-2900 - [c328]George Eskandar, Youssef Farag, Tarun Yenamandra, Daniel Cremers, Karim Guirguis, Bin Yang:
Urban-StyleGAN: Learning to Generate and Manipulate Images of Urban Scenes. IV 2023: 1-8 - [c327]Florian Hofherr, Lukas Koestler, Florian Bernard, Daniel Cremers:
Neural Implicit Representations for Physical Parameter Inference from a Single Video. WACV 2023: 2092-2102 - [c326]Lu Sang, Bjoern Haefner, Xingxing Zuo, Daniel Cremers:
High-Quality RGB-D Reconstruction via Multi-View Uncalibrated Photometric Stereo and Gradient-SDF. WACV 2023: 3105-3114 - [i205]Patrick Wenzel, Nan Yang, Rui Wang, Niclas Zeller, Daniel Cremers:
4Seasons: Benchmarking Visual SLAM and Long-Term Localization for Autonomous Driving in Challenging Conditions. CoRR abs/2301.01147 (2023) - [i204]Dekai Zhu, Qadeer Khan, Daniel Cremers:
Multi-Vehicle Trajectory Prediction at Intersections using State and Intention Information. CoRR abs/2301.02561 (2023) - [i203]Felix Wimbauer, Nan Yang, Christian Rupprecht, Daniel Cremers:
Behind the Scenes: Density Fields for Single View Reconstruction. CoRR abs/2301.07668 (2023) - [i202]Linus Härenstam-Nielsen, Niclas Zeller, Daniel Cremers:
Semidefinite Relaxations for Robust Multiview Triangulation. CoRR abs/2301.11431 (2023) - [i201]Christian Tomani, Futa Waseda, Yuesong Shen, Daniel Cremers:
Beyond In-Domain Scenarios: Robust Density-Aware Calibration. CoRR abs/2302.05118 (2023) - [i200]Thomas Wimmer, Vladimir Golkov, Hoai Nam Dang, Moritz Zaiss, Andreas Maier, Daniel Cremers:
Scale-Equivariant Deep Learning for 3D Data. CoRR abs/2304.05864 (2023) - [i199]Olaf Wysocki, Yan Xia, Magdalena Wysocki, Eleonora Grilli, Ludwig Hoegner, Daniel Cremers, Uwe Stilla:
Scan2LoD3: Reconstructing semantic 3D building models at LoD3 using ray casting and Bayesian networks. CoRR abs/2305.06314 (2023) - [i198]Hoai Nam Dang, Vladimir Golkov, Thomas Wimmer, Daniel Cremers, Andreas K. Maier, Moritz Zaiss:
Joint MR sequence optimization beats pure neural network approaches for spin-echo MRI super-resolution. CoRR abs/2305.07524 (2023) - [i197]Viktoria Ehm, Daniel Cremers, Florian Bernard:
Non-Separable Multi-Dimensional Network Flows for Visual Computing. CoRR abs/2305.08628 (2023) - [i196]Dominik Muhle, Lukas Koestler, Krishna Murthy Jatavallabhula, Daniel Cremers:
Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares. CoRR abs/2305.09527 (2023) - [i195]George Eskandar, Youssef Farag, Tarun Yenamandra, Daniel Cremers, Karim Guirguis, Bin Yang:
Urban-StyleGAN: Learning to Generate and Manipulate Images of Urban Scenes. CoRR abs/2305.09602 (2023) - [i194]Lu Sang, Abhishek Saroha, Maolin Gao, Daniel Cremers:
Weight-Aware Implicit Geometry Reconstruction with Curvature-Guided Sampling. CoRR abs/2306.02099 (2023) - [i193]Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel:
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks. CoRR abs/2307.07753 (2023) - [i192]Marc Botet Colomer, Pier Luigi Dovesi, Theodoros Panagiotakopoulos, Joao Frederico Carvalho, Linus Härenstam-Nielsen, Hossein Azizpour, Hedvig Kjellström, Daniel Cremers, Matteo Poggi:
To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation. CoRR abs/2307.15063 (2023) - [i191]Yining Ma, Qadeer Khan, Daniel Cremers:
Multi Agent Navigation in Unconstrained Environments using a Centralized Attention based Graphical Neural Network Controller. CoRR abs/2307.16727 (2023) - [i190]Jonathan Schmidt, Qadeer Khan, Daniel Cremers:
LiDAR View Synthesis for Robust Vehicle Navigation Without Expert Labels. CoRR abs/2308.01424 (2023) - [i189]Jiaxin Pan, Changyao Zhou, Mariia Gladkova, Qadeer Khan, Daniel Cremers:
Robust Autonomous Vehicle Pursuit without Expert Steering Labels. CoRR abs/2308.08380 (2023) - [i188]Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Möller, Daniel Cremers, Florian Bernard:
SIGMA: Scale-Invariant Global Sparse Shape Matching. CoRR abs/2308.08393 (2023) - [i187]Viktoria Ehm, Paul Roetzer, Marvin Eisenberger, Maolin Gao, Florian Bernard, Daniel Cremers:
Geometrically Consistent Partial Shape Matching. CoRR abs/2309.05013 (2023) - [i186]Yiming Shan, Yan Xia, Yuhong Chen, Daniel Cremers:
SCP: Scene Completion Pre-training for 3D Object Detection. CoRR abs/2309.06199 (2023) - [i185]Christian Koke, Abhishek Saroha, Yuesong Shen, Marvin Eisenberger, Daniel Cremers:
ResolvNet: A Graph Convolutional Network with multi-scale Consistency. CoRR abs/2310.00431 (2023) - [i184]Christian Koke, Daniel Cremers:
HoloNets: Spectral Convolutions do extend to Directed Graphs. CoRR abs/2310.02232 (2023) - [i183]Christian Tomani, David Vilar, Markus Freitag, Colin Cherry, Subhajit Naskar, Mara Finkelstein, Daniel Cremers:
Quality Control at Your Fingertips: Quality-Aware Translation Models. CoRR abs/2310.06707 (2023) - [i182]Adrian Hayler, Felix Wimbauer, Dominik Muhle, Christian Rupprecht, Daniel Cremers:
S4C: Self-Supervised Semantic Scene Completion with Neural Fields. CoRR abs/2310.07522 (2023) - [i181]Ugur Sahin, Hang Li, Qadeer Khan, Daniel Cremers, Volker Tresp:
Enhancing Multimodal Compositional Reasoning of Visual Language Models with Generative Negative Mining. CoRR abs/2311.03964 (2023) - [i180]Yan Xia, Letian Shi, Zifeng Ding, João F. Henriques, Daniel Cremers:
Text2Loc: 3D Point Cloud Localization from Natural Language. CoRR abs/2311.15977 (2023) - [i179]Mreenav Shyam Deka, Lu Sang, Daniel Cremers:
Erasing the Ephemeral: Joint Camera Refinement and Transient Object Removal for Street View Synthesis. CoRR abs/2311.17634 (2023) - [i178]Dávid Komorowicz, Lu Sang, Ferdinand Maiwald, Daniel Cremers:
Coloring the Past: Neural Historical Buildings Reconstruction from Archival Photography. CoRR abs/2311.17810 (2023) - [i177]Felix Wimbauer, Bichen Wu, Edgar Schönfeld, Xiaoliang Dai, Ji Hou, Zijian He, Artsiom Sanakoyeu, Peizhao Zhang, Sam S. Tsai, Jonas Kohler, Christian Rupprecht, Daniel Cremers, Peter Vajda, Jialiang Wang:
Cache Me if You Can: Accelerating Diffusion Models through Block Caching. CoRR abs/2312.03209 (2023) - [i176]Simon Klenk, Marvin Motzet, Lukas Koestler, Daniel Cremers:
Deep Event Visual Odometry. CoRR abs/2312.09800 (2023) - 2022
- [j87]Hamid Rezatofighi, Tianyu Zhu, Roman Kaskman, Farbod T. Motlagh, Javen Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid:
Learn to Predict Sets Using Feed-Forward Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9011-9025 (2022) - [j86]Lukas von Stumberg, Daniel Cremers:
DM-VIO: Delayed Marginalization Visual-Inertial Odometry. IEEE Robotics Autom. Lett. 7(2): 1408-1415 (2022) - [j85]Hartmut Bauermeister, Emanuel Laude, Thomas Möllenhoff, Michael Möller, Daniel Cremers:
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. SIAM J. Imaging Sci. 15(3): 1253-1281 (2022) - [c325]Zhenzhang Ye, Tarun Yenamandra, Florian Bernard, Daniel Cremers:
Joint Deep Multi-Graph Matching and 3D Geometry Learning from Inhomogeneous 2D Image Collections. AAAI 2022: 3125-3133 - [c324]Hang Li, Qadeer Khan, Volker Tresp, Daniel Cremers:
Biologically Inspired Neural Path Finding. BI 2022: 329-342 - [c323]Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer:
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRL 2022: 161-174 - [c322]Paul Roetzer, Paul Swoboda, Daniel Cremers, Florian Bernard:
A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching. CVPR 2022: 428-438 - [c321]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Florian Bernard, Daniel Cremers:
A Unified Framework for Implicit Sinkhorn Differentiation. CVPR 2022: 499-508 - [c320]Dominik Muhle, Lukas Koestler, Nikolaus Demmel, Florian Bernard, Daniel Cremers:
The Probabilistic Normal Epipolar Constraint for Frame- To-Frame Rotation Optimization under Uncertain Feature Positions. CVPR 2022: 1809-1818 - [c319]Christiane Sommer, Lu Sang, David Schubert, Daniel Cremers:
Gradient-SDF: A Semi-Implicit Surface Representation for 3D Reconstruction. CVPR 2022: 6270-6279 - [c318]Aysim Toker, Lukas Kondmann, Mark Weber, Marvin Eisenberger, Andrés Camero, Jingliang Hu, Ariadna Pregel Hoderlein, Çaglar Senaras, Timothy Davis, Daniel Cremers, Giovanni Marchisio, Xiao Xiang Zhu, Laura Leal-Taixé:
DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation. CVPR 2022: 21126-21135 - [c317]Christian Tomani, Daniel Cremers, Florian Buettner:
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. ECCV (13) 2022: 555-569 - [c316]Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner:
Intrinsic Neural Fields: Learning Functions on Manifolds. ECCV (2) 2022: 622-639 - [c315]Dominik Rößle, Daniel Cremers, Torsten Schön:
Perceiver Hopfield Pooling for Dynamic Multi-modal and Multi-instance Fusion. ICANN (1) 2022: 599-610 - [c314]Deepan Das, Qadeer Khan, Daniel Cremers:
Ventriloquist-Net: Leveraging Speech Cues for Emotive Talking Head Generation. ICIP 2022: 1716-1720 - [c313]Zhakshylyk Nurlanov, Daniel Cremers, Florian Bernard:
Efficient and Flexible Sublabel-Accurate Energy Minimization. ICPR 2022: 175-181 - [c312]Florian Müller, Qadeer Khan, Daniel Cremers:
Lateral Ego-Vehicle Control Without Supervision Using Point Clouds. ICPRAI (1) 2022: 477-488 - [c311]Qing Cheng, Niclas Zeller, Daniel Cremers:
Vision-Based Large-scale 3D Semantic Mapping for Autonomous Driving Applications. ICRA 2022: 9235-9242 - [c310]Mariia Gladkova, Nikita Korobov, Nikolaus Demmel, Aljosa Osep, Laura Leal-Taixé, Daniel Cremers:
DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment. IROS 2022: 3777-3784 - [c309]Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers:
What Makes Graph Neural Networks Miscalibrated? NeurIPS 2022 - [c308]Yuesong Shen, Daniel Cremers:
Deep Combinatorial Aggregation. NeurIPS 2022 - [e12]Björn Andres, Florian Bernard, Daniel Cremers, Simone Frintrop, Bastian Goldlücke, Ivo Ihrke:
Pattern Recognition - 44th DAGM German Conference, DAGM GCPR 2022, Konstanz, Germany, September 27-30, 2022, Proceedings. Lecture Notes in Computer Science 13485, Springer 2022, ISBN 978-3-031-16787-4 [contents] - [i175]Lukas von Stumberg, Daniel Cremers:
DM-VIO: Delayed Marginalization Visual-Inertial Odometry. CoRR abs/2201.04114 (2022) - [i174]Qing Cheng, Niclas Zeller, Daniel Cremers:
Vision-based Large-scale 3D Semantic Mapping for Autonomous Driving Applications. CoRR abs/2203.01087 (2022) - [i173]Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner:
Intrinsic Neural Fields: Learning Functions on Manifolds. CoRR abs/2203.07967 (2022) - [i172]Florian Müller, Qadeer Khan, Daniel Cremers:
Lateral Ego-Vehicle Control without Supervision using Point Clouds. CoRR abs/2203.10662 (2022) - [i171]Aysim Toker, Lukas Kondmann, Mark Weber, Marvin Eisenberger, Andrés Camero, Jingliang Hu, Ariadna Pregel Hoderlein, Çaglar Senaras, Timothy Davis, Daniel Cremers, Giovanni Marchisio, Xiao Xiang Zhu, Laura Leal-Taixé:
DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation. CoRR abs/2203.12560 (2022) - [i170]Tarun Yenamandra, Ayush Tewari, Nan Yang, Florian Bernard, Christian Theobalt, Daniel Cremers:
HDSDF: Hybrid Directional and Signed Distance Functions for Fast Inverse Rendering. CoRR abs/2203.16284 (2022) - [i169]Dominik Muhle, Lukas Koestler, Nikolaus Demmel, Florian Bernard, Daniel Cremers:
The Probabilistic Normal Epipolar Constraint for Frame-To-Frame Rotation Optimization under Uncertain Feature Positions. CoRR abs/2204.02256 (2022) - [i168]Abhishek Saroha, Marvin Eisenberger, Tarun Yenamandra, Daniel Cremers:
Implicit Shape Completion via Adversarial Shape Priors. CoRR abs/2204.10060 (2022) - [i167]Paul Roetzer, Paul Swoboda, Daniel Cremers, Florian Bernard:
A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching. CoRR abs/2204.12805 (2022) - [i166]Simon Weber, Nikolaus Demmel, Daniel Cremers:
Power Bundle Adjustment for Large-Scale 3D Reconstruction. CoRR abs/2204.12834 (2022) - [i165]Florian Hofherr, Lukas Koestler, Florian Bernard, Daniel Cremers:
Neural Implicit Representations for Physical Parameter Inference from a Single Video. CoRR abs/2204.14030 (2022) - [i164]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Florian Bernard, Daniel Cremers:
A Unified Framework for Implicit Sinkhorn Differentiation. CoRR abs/2205.06688 (2022) - [i163]Michael Schleiss, Fahmi Rouatbi, Daniel Cremers:
VPAIR - Aerial Visual Place Recognition and Localization in Large-scale Outdoor Environments. CoRR abs/2205.11567 (2022) - [i162]Christian Tomani, Daniel Cremers:
CHALLENGER: Training with Attribution Maps. CoRR abs/2205.15094 (2022) - [i161]Hang Li, Qadeer Khan, Volker Tresp, Daniel Cremers:
Biologically Inspired Neural Path Finding. CoRR abs/2206.05971 (2022) - [i160]Zhakshylyk Nurlanov, Daniel Cremers, Florian Bernard:
Efficient and Flexible Sublabel-Accurate Energy Minimization. CoRR abs/2206.09596 (2022) - [i159]Sherwin Bahmani, Oliver Hahn, Eduard Zamfir, Nikita Araslanov, Daniel Cremers, Stefan Roth:
Semantic Self-adaptation: Enhancing Generalization with a Single Sample. CoRR abs/2208.05788 (2022) - [i158]Simon Klenk, Lukas Koestler, Davide Scaramuzza, Daniel Cremers:
E-NeRF: Neural Radiance Fields from a Moving Event Camera. CoRR abs/2208.11300 (2022) - [i157]Mariia Gladkova, Nikita Korobov, Nikolaus Demmel, Aljosa Osep, Laura Leal-Taixé, Daniel Cremers:
DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment. CoRR abs/2209.14965 (2022) - [i156]Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers:
What Makes Graph Neural Networks Miscalibrated? CoRR abs/2210.06391 (2022) - [i155]Yuesong Shen, Daniel Cremers:
Deep Combinatorial Aggregation. CoRR abs/2210.06436 (2022) - [i154]Lu Sang, Bjoern Haefner, Xingxing Zuo, Daniel Cremers:
High-Quality RGB-D Reconstruction via Multi-View Uncalibrated Photometric Stereo and Gradient-SDF. CoRR abs/2210.12202 (2022) - [i153]Hans Hao-Hsun Hsu, Yuesong Shen, Daniel Cremers:
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on Graphs. CoRR abs/2210.15575 (2022) - [i152]Yan Xia, Mariia Gladkova, Rui Wang, João F. Henriques, Daniel Cremers, Uwe Stilla:
PVT3D: Point Voxel Transformers for Place Recognition from Sparse Lidar Scans. CoRR abs/2211.12542 (2022) - [i151]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
G-MSM: Unsupervised Multi-Shape Matching with Graph-based Affinity Priors. CoRR abs/2212.02910 (2022) - [i150]Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer:
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRR abs/2212.02988 (2022) - [i149]Mohammed Brahimi, Bjoern Haefner, Tarun Yenamandra, Bastian Goldluecke, Daniel Cremers:
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering. CoRR abs/2212.04968 (2022) - [i148]Simon Klenk, David Bonello, Lukas Koestler, Daniel Cremers:
Masked Event Modeling: Self-Supervised Pretraining for Event Cameras. CoRR abs/2212.10368 (2022) - 2021
- [j84]Patrick Dendorfer, Aljosa Osep, Anton Milan, Konrad Schindler, Daniel Cremers, Ian Reid, Stefan Roth, Laura Leal-Taixé:
MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking. Int. J. Comput. Vis. 129(4): 845-881 (2021) - [c307]Bjoern Haefner, Simon Green, Alan Oursland, Daniel Andersen, Michael Goesele, Daniel Cremers, Richard A. Newcombe, Thomas Whelan:
Recovering Real-World Reflectance Properties and Shading From HDR Imagery. 3DV 2021: 1075-1084 - [c306]Viktoria Ehm, Daniel Cremers, Florian Bernard:
Shortest Paths in Graphs with Matrix-Valued Edges: Concepts, Algorithm and Application to 3D Multi-Shape Analysis. 3DV 2021: 1186-1195 - [c305]Qadeer Khan, Patrick Wenzel, Daniel Cremers:
Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry. AISTATS 2021: 3781-3789 - [c304]Lukas Koestler, Nan Yang, Niclas Zeller, Daniel Cremers:
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo. CoRL 2021: 34-45 - [c303]Felix Wimbauer, Nan Yang, Lukas von Stumberg, Niclas Zeller, Daniel Cremers:
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments From a Single Moving Camera. CVPR 2021: 6112-6122 - [c302]Marvin Eisenberger, David Novotný, Gael Kerchenbaum, Patrick Labatut, Natalia Neverova, Daniel Cremers, Andrea Vedaldi:
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go. CVPR 2021: 7473-7483 - [c301]Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner:
Post-Hoc Uncertainty Calibration for Domain Drift Scenarios. CVPR 2021: 10124-10132 - [c300]Yan Xia, Yusheng Xu, Shuang Li, Rui Wang, Juan Du, Daniel Cremers, Uwe Stilla:
SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud Based Place Recognition. CVPR 2021: 11348-11357 - [c299]Nikolaus Demmel, Christiane Sommer, Daniel Cremers, Vladyslav Usenko:
Square Root Bundle Adjustment for Large-Scale Reconstruction. CVPR 2021: 11723-11732 - [c298]Tarun Yenamandra, Ayush Tewari, Florian Bernard, Hans-Peter Seidel, Mohamed Elgharib, Daniel Cremers, Christian Theobalt:
i3DMM: Deep Implicit 3D Morphable Model of Human Heads. CVPR 2021: 12803-12813 - [c297]Maolin Gao, Zorah Lähner, Johan Thunberg, Daniel Cremers, Florian Bernard:
Isometric Multi-Shape Matching. CVPR 2021: 14183-14193 - [c296]Zhenzhang Ye, Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff, Daniel Cremers:
Sublabel-Accurate Multilabeling Meets Product Label Spaces. GCPR 2021: 3-17 - [c295]Simon Weber, Nikolaus Demmel, Daniel Cremers:
Multidirectional Conjugate Gradients for Scalable Bundle Adjustment. GCPR 2021: 712-724 - [c294]Nikolaus Demmel, David Schubert, Christiane Sommer, Daniel Cremers, Vladyslav Usenko:
Square Root Marginalization for Sliding-Window Bundle Adjustment. ICCV 2021: 13240-13248 - [c293]Thomas Frerix, Dmitrii Kochkov, Jamie A. Smith, Daniel Cremers, Michael P. Brenner, Stephan Hoyer:
Variational Data Assimilation with a Learned Inverse Observation Operator. ICML 2021: 3449-3458 - [c292]Mariia Gladkova, Rui Wang, Niclas Zeller, Daniel Cremers:
Tight Integration of Feature-based Relocalization in Monocular Direct Visual Odometry. ICRA 2021: 9608-9614 - [c291]Patrick Wenzel, Torsten Schön, Laura Leal-Taixé, Daniel Cremers:
Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning. ICRA 2021: 14360-14366 - [c290]Simon Klenk, Jason Chui, Nikolaus Demmel, Daniel Cremers:
TUM-VIE: The TUM Stereo Visual-Inertial Event Dataset. IROS 2021: 8601-8608 - [c289]Martin Wudenka, Marcus Gerhard Müller, Nikolaus Demmel, Armin Wedler, Rudolph Triebel, Daniel Cremers, Wolfgang Stürzl:
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions. IROS 2021: 8737-8744 - [c288]Florian Bernard, Daniel Cremers, Johan Thunberg:
Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation. NeurIPS 2021: 25256-25266 - [c287]Mark Weber, Jun Xie, Maxwell D. Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljosa Osep, Laura Leal-Taixé, Liang-Chieh Chen:
STEP: Segmenting and Tracking Every Pixel. NeurIPS Datasets and Benchmarks 2021 - [c286]Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs:
Bregman Proximal Gradient Algorithms for Deep Matrix Factorization. SSVM 2021: 204-215 - [c285]Yu Wang, Yuesong Shen, Daniel Cremers:
Explicit pairwise factorized graph neural network for semi-supervised node classification. UAI 2021: 1979-1987 - [i147]Mariia Gladkova, Rui Wang, Niclas Zeller, Daniel Cremers:
Tight Integration of Feature-Based Relocalization in Monocular Direct Visual Odometry. CoRR abs/2102.01191 (2021) - [i146]Philip Müller, Vladimir Golkov, Valentina Tomassini, Daniel Cremers:
Rotation-Equivariant Deep Learning for Diffusion MRI. CoRR abs/2102.06942 (2021) - [i145]Thomas Frerix, Dmitrii Kochkov, Jamie A. Smith, Daniel Cremers, Michael P. Brenner, Stephan Hoyer:
Variational Data Assimilation with a Learned Inverse Observation Operator. CoRR abs/2102.11192 (2021) - [i144]Mark Weber, Jun Xie, Maxwell D. Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljosa Osep, Laura Leal-Taixé, Liang-Chieh Chen:
STEP: Segmenting and Tracking Every Pixel. CoRR abs/2102.11859 (2021) - [i143]Christian Tomani, Daniel Cremers, Florian Buettner:
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. CoRR abs/2102.12182 (2021) - [i142]Nikolaus Demmel, Christiane Sommer, Daniel Cremers, Vladyslav Usenko:
Square Root Bundle Adjustment for Large-Scale Reconstruction. CoRR abs/2103.01843 (2021) - [i141]Patrick Wenzel, Torsten Schön, Laura Leal-Taixé, Daniel Cremers:
Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning. CoRR abs/2103.04727 (2021) - [i140]Qadeer Khan, Patrick Wenzel, Daniel Cremers:
Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry. CoRR abs/2103.11204 (2021) - [i139]Zhenzhang Ye, Tarun Yenamandra, Florian Bernard, Daniel Cremers:
Joint Deep Multi-Graph Matching and 3D Geometry Learning from Inhomogeneous 2D Image Collections. CoRR abs/2103.17229 (2021) - [i138]Marvin Eisenberger, David Novotný, Gael Kerchenbaum, Patrick Labatut, Natalia Neverova, Daniel Cremers, Andrea Vedaldi:
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go. CoRR abs/2106.09431 (2021) - [i137]Mark Weber, Huiyu Wang, Siyuan Qiao, Jun Xie, Maxwell D. Collins, Yukun Zhu, Liangzhe Yuan, Dahun Kim, Qihang Yu, Daniel Cremers, Laura Leal-Taixé, Alan L. Yuille, Florian Schroff, Hartwig Adam, Liang-Chieh Chen:
DeepLab2: A TensorFlow Library for Deep Labeling. CoRR abs/2106.09748 (2021) - [i136]Jason Chui, Simon Klenk, Daniel Cremers:
Event-Based Feature Tracking in Continuous Time with Sliding Window Optimization. CoRR abs/2107.04536 (2021) - [i135]Hartmut Bauermeister, Emanuel Laude, Thomas Möllenhoff, Michael Möller, Daniel Cremers:
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. CoRR abs/2107.06028 (2021) - [i134]Yu Wang, Yuesong Shen, Daniel Cremers:
Explicit Pairwise Factorized Graph Neural Network for Semi-Supervised Node Classification. CoRR abs/2107.13059 (2021) - [i133]Simon Klenk, Jason Chui, Nikolaus Demmel, Daniel Cremers:
TUM-VIE: The TUM Stereo Visual-Inertial Event Dataset. CoRR abs/2108.07329 (2021) - [i132]Ji Yang, Lu Sang, Daniel Cremers:
Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry. CoRR abs/2109.01461 (2021) - [i131]Nikolaus Demmel, David Schubert, Christiane Sommer, Daniel Cremers, Vladyslav Usenko:
Square Root Marginalization for Sliding-Window Bundle Adjustment. CoRR abs/2109.02182 (2021) - [i130]Martin Wudenka, Marcus Gerhard Müller, Nikolaus Demmel, Armin Wedler, Rudolph Triebel, Daniel Cremers, Wolfgang Stürzl:
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions. CoRR abs/2109.05509 (2021) - [i129]Maximilian Mozes, Martin Schmitt, Vladimir Golkov, Hinrich Schütze, Daniel Cremers:
Scene Graph Generation for Better Image Captioning? CoRR abs/2109.11398 (2021) - [i128]Florian Bernard, Daniel Cremers, Johan Thunberg:
Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation. CoRR abs/2110.00053 (2021) - [i127]Simon Weber, Nikolaus Demmel, Daniel Cremers:
Multidirectional Conjugate Gradients for Scalable Bundle Adjustment. CoRR abs/2110.04015 (2021) - [i126]Lukas Koestler, Nan Yang, Niclas Zeller, Daniel Cremers:
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo. CoRR abs/2111.07418 (2021) - [i125]Christiane Sommer, Lu Sang, David Schubert, Daniel Cremers:
Gradient-SDF: A Semi-Implicit Surface Representation for 3D Reconstruction. CoRR abs/2111.13652 (2021) - [i124]Viktoria Ehm, Daniel Cremers, Florian Bernard:
Shortest Paths in Graphs with Matrix-Valued Edges: Concepts, Algorithm and Application to 3D Multi-Shape Analysis. CoRR abs/2112.04165 (2021) - 2020
- [j83]Emanuel Laude, Peter Ochs, Daniel Cremers:
Bregman Proximal Mappings and Bregman-Moreau Envelopes Under Relative Prox-Regularity. J. Optim. Theory Appl. 184(3): 724-761 (2020) - [j82]Bjoern Haefner, Songyou Peng, Alok Verma, Yvain Quéau, Daniel Cremers:
Photometric Depth Super-Resolution. IEEE Trans. Pattern Anal. Mach. Intell. 42(10): 2453-2464 (2020) - [j81]Vladyslav Usenko, Nikolaus Demmel, David Schubert, Jörg Stückler, Daniel Cremers:
Visual-Inertial Mapping With Non-Linear Factor Recovery. IEEE Robotics Autom. Lett. 5(2): 422-429 (2020) - [j80]Lukas von Stumberg, Patrick Wenzel, Qadeer Khan, Daniel Cremers:
GN-Net: The Gauss-Newton Loss for Multi-Weather Relocalization. IEEE Robotics Autom. Lett. 5(2): 890-897 (2020) - [j79]Christiane Sommer, Yumin Sun, Leonidas J. Guibas, Daniel Cremers, Tolga Birdal:
From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds. IEEE Robotics Autom. Lett. 5(2): 1764-1771 (2020) - [c284]Nikolaus Demmel, Maolin Gao, Emanuel Laude, Tao Wu, Daniel Cremers:
Distributed Photometric Bundle Adjustment. 3DV 2020: 140-149 - [c283]Benjamin Holzschuh, Zorah Lähner, Daniel Cremers:
Simulated Annealing for 3D Shape Correspondence. 3DV 2020: 252-260 - [c282]Mehmet Aygün, Zorah Lähner, Daniel Cremers:
Unsupervised Dense Shape Correspondence using Heat Kernels. 3DV 2020: 573-582 - [c281]Vladimir Golkov, Marcin J. Skwark, Atanas Mirchev, Georgi Dikov, Alexander R. Geanes, Jeffrey L. Mendenhall, Jens Meiler, Daniel Cremers:
3D Deep Learning for Biological Function Prediction from Physical Fields. 3DV 2020: 928-937 - [c280]Lukas von Stumberg, Patrick Wenzel, Nan Yang, Daniel Cremers:
LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization. 3DV 2020: 968-977 - [c279]Zhenzhang Ye, Thomas Möllenhoff, Tao Wu, Daniel Cremers:
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning. AISTATS 2020: 657-668 - [c278]Nan Yang, Lukas von Stumberg, Rui Wang, Daniel Cremers:
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry. CVPR 2020: 1278-1289 - [c277]Thomas Frerix, Matthias Nießner, Daniel Cremers:
Homogeneous Linear Inequality Constraints for Neural Network Activations. CVPR Workshops 2020: 3229-3234 - [c276]Sebastian Weiss, Robert Maier, Daniel Cremers, Rüdiger Westermann, Nils Thuerey:
Correspondence-Free Material Reconstruction using Sparse Surface Constraints. CVPR 2020: 4685-4694 - [c275]Christiane Sommer, Vladyslav Usenko, David Schubert, Nikolaus Demmel, Daniel Cremers:
Efficient Derivative Computation for Cumulative B-Splines on Lie Groups. CVPR 2020: 11145-11153 - [c274]Marvin Eisenberger, Zorah Lähner, Daniel Cremers:
Smooth Shells: Multi-Scale Shape Registration With Functional Maps. CVPR 2020: 12262-12271 - [c273]Lukas Koestler, Nan Yang, Rui Wang, Daniel Cremers:
Learning Monocular 3D Vehicle Detection Without 3D Bounding Box Labels. GCPR 2020: 116-129 - [c272]Patrick Wenzel, Rui Wang, Nan Yang, Qing Cheng, Qadeer Khan, Lukas von Stumberg, Niclas Zeller, Daniel Cremers:
4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving. GCPR 2020: 404-417 - [c271]Marvin Eisenberger, Daniel Cremers:
Hamiltonian Dynamics for Real-World Shape Interpolation. ECCV (4) 2020: 179-196 - [c270]Juan Du, Rui Wang, Daniel Cremers:
DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization. ECCV (4) 2020: 744-762 - [c269]Christiane Sommer, Yumin Sun, Erik Bylow, Daniel Cremers:
PrimiTect: Fast Continuous Hough Voting for Primitive Detection. ICRA 2020: 8404-8410 - [c268]Rui Wang, Nan Yang, Jörg Stückler, Daniel Cremers:
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation. ICRA 2020: 11067-11073 - [c267]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport. NeurIPS 2020 - [c266]Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Effective Version Space Reduction for Convolutional Neural Networks. ECML/PKDD (2) 2020: 85-100 - [c265]Lu Sang, Bjoern Haefner, Daniel Cremers:
Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach. WACV 2020: 1-10 - [p9]Vladyslav Usenko, Lukas von Stumberg, Jörg Stückler, Daniel Cremers:
TUM Flyers: Vision - Based MAV Navigation for Systematic Inspection of Structures. EuRoC 2020: 189-209 - [i123]Christiane Sommer, Yumin Sun, Leonidas J. Guibas, Daniel Cremers, Tolga Birdal:
From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds. CoRR abs/2001.07360 (2020) - [i122]Hamid Rezatofighi, Roman Kaskman, Farbod T. Motlagh, Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid:
Learn to Predict Sets Using Feed-Forward Neural Networks. CoRR abs/2001.11845 (2020) - [i121]Zhenzhang Ye, Thomas Möllenhoff, Tao Wu, Daniel Cremers:
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning. CoRR abs/2002.12236 (2020) - [i120]Nan Yang, Lukas von Stumberg, Rui Wang, Daniel Cremers:
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry. CoRR abs/2003.01060 (2020) - [i119]Patrick Dendorfer, Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian D. Reid, Stefan Roth, Konrad Schindler, Laura Leal-Taixé:
MOT20: A benchmark for multi object tracking in crowded scenes. CoRR abs/2003.09003 (2020) - [i118]Marvin Eisenberger, Daniel Cremers:
Hamiltonian Dynamics for Real-World Shape Interpolation. CoRR abs/2004.05199 (2020) - [i117]Christiane Sommer, Yumin Sun, Erik Bylow, Daniel Cremers:
PrimiTect: Fast Continuous Hough Voting for Primitive Detection. CoRR abs/2005.07457 (2020) - [i116]Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Effective Version Space Reduction for Convolutional Neural Networks. CoRR abs/2006.12456 (2020) - [i115]Yuesong Shen, Daniel Cremers:
Deriving Neural Network Design and Learning from the Probabilistic Framework of Chain Graphs. CoRR abs/2006.16856 (2020) - [i114]Vladimir Golkov, Alexander Becker, Daniel T. Plop, Daniel Cuturilo, Neda Davoudi, Jeffrey L. Mendenhall, Rocco Moretti, Jens Meiler, Daniel Cremers:
Deep Learning for Virtual Screening: Five Reasons to Use ROC Cost Functions. CoRR abs/2007.07029 (2020) - [i113]Juan Du, Rui Wang, Daniel Cremers:
DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization. CoRR abs/2007.09217 (2020) - [i112]Patrick Wenzel, Rui Wang, Nan Yang, Qing Cheng, Qadeer Khan, Lukas von Stumberg, Niclas Zeller, Daniel Cremers:
4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving. CoRR abs/2009.06364 (2020) - [i111]Lukas Koestler, Nan Yang, Rui Wang, Daniel Cremers:
Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels. CoRR abs/2010.03506 (2020) - [i110]Lukas von Stumberg, Patrick Wenzel, Nan Yang, Daniel Cremers:
LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization. CoRR abs/2010.06323 (2020) - [i109]Patrick Dendorfer, Aljosa Osep, Anton Milan, Konrad Schindler, Daniel Cremers, Ian D. Reid, Stefan Roth, Laura Leal-Taixé:
MOTChallenge: A Benchmark for Single-camera Multiple Target Tracking. CoRR abs/2010.07548 (2020) - [i108]Mehmet Aygün, Zorah Lähner, Daniel Cremers:
Unsupervised Dense Shape Correspondence using Heat Kernels. CoRR abs/2010.12682 (2020) - [i107]Giorgio Fabbro, Vladimir Golkov, Thomas Kemp, Daniel Cremers:
Speech Synthesis and Control Using Differentiable DSP. CoRR abs/2010.15084 (2020) - [i106]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport. CoRR abs/2010.15261 (2020) - [i105]Felix Wimbauer, Nan Yang, Lukas von Stumberg, Niclas Zeller, Daniel Cremers:
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera. CoRR abs/2011.11814 (2020) - [i104]Yan Xia, Yusheng Xu, Shuang Li, Rui Wang, Juan Du, Daniel Cremers, Uwe Stilla:
SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition. CoRR abs/2011.12430 (2020) - [i103]Or Litany, Emanuele Rodolà, Alex M. Bronstein, Michael M. Bronstein, Daniel Cremers:
Non-Rigid Puzzles. CoRR abs/2011.13076 (2020) - [i102]Tarun Yenamandra, Ayush Tewari, Florian Bernard, Hans-Peter Seidel, Mohamed Elgharib, Daniel Cremers, Christian Theobalt:
i3DMM: Deep Implicit 3D Morphable Model of Human Heads. CoRR abs/2011.14143 (2020) - [i101]Maolin Gao, Zorah Lähner, Johan Thunberg, Daniel Cremers, Florian Bernard:
Isometric Multi-Shape Matching. CoRR abs/2012.02689 (2020) - [i100]Ioannis Chiotellis, Daniel Cremers:
Neural Online Graph Exploration. CoRR abs/2012.03345 (2020) - [i99]Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner:
Post-hoc Uncertainty Calibration for Domain Drift Scenarios. CoRR abs/2012.10988 (2020)
2010 – 2019
- 2019
- [j78]Marvin Eisenberger, Zorah Lähner, Daniel Cremers:
Divergence-Free Shape Correspondence by Deformation. Comput. Graph. Forum 38(5): 1-12 (2019) - [j77]Kevis-Kokitsi Maninis, Sergi Caelles, Yuhua Chen, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
Video Object Segmentation without Temporal Information. IEEE Trans. Pattern Anal. Mach. Intell. 41(6): 1515-1530 (2019) - [j76]Henning Tjaden, Ulrich Schwanecke, Elmar Schömer, Daniel Cremers:
A Region-Based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking. IEEE Trans. Pattern Anal. Mach. Intell. 41(8): 1797-1812 (2019) - [c264]Bjoern Haefner, Yvain Quéau, Daniel Cremers:
Photometric Segmentation: Simultaneous Photometric Stereo and Masking. 3DV 2019: 222-229 - [c263]Roberto M. Dyke, C. Stride, Yu-Kun Lai, Paul L. Rosin, Mathieu Aubry, Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers, Matthew Fisher, Thibault Groueix, Daoliang Guo, Vladimir G. Kim, Ron Kimmel, Zorah Lähner, Kun Li, Or Litany, Tal Remez, Emanuele Rodolà, Bryan C. Russell, Yusuf Sahillioglu, Ron Slossberg, Gary K. L. Tam, Matthias Vestner, Z. Wu, Jingyu Yang:
Shape Correspondence with Isometric and Non-Isometric Deformations. 3DOR@Eurographics 2019: 111-119 - [c262]Emanuel Laude, Tao Wu, Daniel Cremers:
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems. AISTATS 2019: 547-556 - [c261]Eunah Jung, Nan Yang, Daniel Cremers:
Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light. CoRL 2019: 651-660 - [c260]Thomas Möllenhoff, Daniel Cremers:
Lifting Vectorial Variational Problems: A Natural Formulation Based on Geometric Measure Theory and Discrete Exterior Calculus. CVPR 2019: 11117-11126 - [c259]Michael Möller, Thomas Möllenhoff, Daniel Cremers:
Controlling Neural Networks via Energy Dissipation. ICCV 2019: 3255-3264 - [c258]Zhenzhang Ye, Bjoern Haefner, Maolin Gao, Tao Wu, Yvain Quéau, Daniel Cremers:
Variational Uncalibrated Photometric Stereo Under General Lighting. ICCV 2019: 8538-8547 - [c257]Thomas Möllenhoff, Daniel Cremers:
Flat Metric Minimization with Applications in Generative Modeling. ICML 2019: 4626-4635 - [c256]David Schubert, Nikolaus Demmel, Lukas von Stumberg, Vladyslav Usenko, Daniel Cremers:
Rolling-Shutter Modelling for Direct Visual-Inertial Odometry. IROS 2019: 2462-2469 - [c255]Qadeer Khan, Patrick Wenzel, Daniel Cremers, Laura Leal-Taixé:
Towards Generalizing Sensorimotor Control Across Weather Conditions. IROS 2019: 4497-4503 - [i98]Yuesong Shen, Tao Wu, Csaba Domokos, Daniel Cremers:
Probabilistic Discriminative Learning with Layered Graphical Models. CoRR abs/1902.00057 (2019) - [i97]Thomas Frerix, Matthias Nießner, Daniel Cremers:
Linear Inequality Constraints for Neural Network Activations. CoRR abs/1902.01785 (2019) - [i96]Emanuel Laude, Tao Wu, Daniel Cremers:
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems. CoRR abs/1903.11690 (2019) - [i95]Michael Möller, Thomas Möllenhoff, Daniel Cremers:
Controlling Neural Networks via Energy Dissipation. CoRR abs/1904.03081 (2019) - [i94]Bjoern Haefner, Zhenzhang Ye, Maolin Gao, Tao Wu, Yvain Quéau, Daniel Cremers:
Variational Uncalibrated Photometric Stereo under General Lighting. CoRR abs/1904.03942 (2019) - [i93]Vladyslav Usenko, Nikolaus Demmel, David Schubert, Jörg Stückler, Daniel Cremers:
Visual-Inertial Mapping with Non-Linear Factor Recovery. CoRR abs/1904.06504 (2019) - [i92]Rui Wang, Nan Yang, Jörg Stückler, Daniel Cremers:
DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation. CoRR abs/1904.10097 (2019) - [i91]Lukas von Stumberg, Patrick Wenzel, Qadeer Khan, Daniel Cremers:
GN-Net: The Gauss-Newton Loss for Deep Direct SLAM. CoRR abs/1904.11932 (2019) - [i90]Thomas Möllenhoff, Daniel Cremers:
Lifting Vectorial Variational Problems: A Natural Formulation based on Geometric Measure Theory and Discrete Exterior Calculus. CoRR abs/1905.00851 (2019) - [i89]Jan Schuchardt, Vladimir Golkov, Daniel Cremers:
Learning to Evolve. CoRR abs/1905.03389 (2019) - [i88]Thomas Möllenhoff, Daniel Cremers:
Flat Metric Minimization with Applications in Generative Modeling. CoRR abs/1905.04730 (2019) - [i87]Marvin Eisenberger, Zorah Lähner, Daniel Cremers:
Smooth Shells: Multi-Scale Shape Registration with Functional Maps. CoRR abs/1905.12512 (2019) - [i86]Patrick Dendorfer, Seyed Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian D. Reid, Stefan Roth, Konrad Schindler, Laura Leal-Taixé:
CVPR19 Tracking and Detection Challenge: How crowded can it get? CoRR abs/1906.04567 (2019) - [i85]Qadeer Khan, Patrick Wenzel, Daniel Cremers, Laura Leal-Taixé:
Towards Generalizing Sensorimotor Control Across Weather Conditions. CoRR abs/1907.11025 (2019) - [i84]Thomas Vogt, Evgeny Strekalovskiy, Daniel Cremers, Jan Lellmann:
Lifting methods for manifold-valued variational problems. CoRR abs/1908.03776 (2019) - [i83]Sebastian Weiss, Robert Maier, Rüdiger Westermann, Daniel Cremers, Nils Thuerey:
Sparse Surface Constraints for Combining Physics-based Elasticity Simulation and Correspondence-Free Object Reconstruction. CoRR abs/1910.01812 (2019) - [i82]Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs:
Bregman Proximal Framework for Deep Linear Neural Networks. CoRR abs/1910.03638 (2019) - [i81]Eunah Jung, Nan Yang, Daniel Cremers:
Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light. CoRR abs/1910.06632 (2019) - [i80]Luca Della Libera, Vladimir Golkov, Yue Zhu, Arman Mielke, Daniel Cremers:
Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods. CoRR abs/1910.14594 (2019) - [i79]David Schubert, Nikolaus Demmel, Lukas von Stumberg, Vladyslav Usenko, Daniel Cremers:
Rolling-Shutter Modelling for Direct Visual-Inertial Odometry. CoRR abs/1911.01015 (2019) - [i78]Mohammed Brahimi, Yvain Quéau, Bjoern Haefner, Daniel Cremers:
On the well-posedness of uncalibrated photometric stereo under general lighting. CoRR abs/1911.07268 (2019) - [i77]Christiane Sommer, Vladyslav Usenko, David Schubert, Nikolaus Demmel, Daniel Cremers:
Efficient Derivative Computation for Cumulative B-Splines on Lie Groups. CoRR abs/1911.08860 (2019) - [i76]Pierre Bréchet, Tao Wu, Thomas Möllenhoff, Daniel Cremers:
Informative GANs via Structured Regularization of Optimal Transport. CoRR abs/1912.02160 (2019) - [i75]Lu Sang, Bjoern Haefner, Daniel Cremers:
Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach. CoRR abs/1912.06501 (2019) - 2018
- [j75]Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox:
What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? Int. J. Comput. Vis. 126(9): 942-960 (2018) - [j74]Yvain Quéau, Bastien Durix, Tao Wu, Daniel Cremers, François Lauze, Jean-Denis Durou:
LED-Based Photometric Stereo: Modeling, Calibration and Numerical Solution. J. Math. Imaging Vis. 60(3): 313-340 (2018) - [j73]Jean Mélou, Yvain Quéau, Jean-Denis Durou, Fabien Castan, Daniel Cremers:
Variational Reflectance Estimation from Multi-view Images. J. Math. Imaging Vis. 60(9): 1527-1546 (2018) - [j72]Björn Bringmann, Daniel Cremers, Felix Krahmer, Michael Möller:
The homotopy method revisited: Computing solution paths of ℓ1-regularized problems. Math. Comput. 87(313): 2343-2364 (2018) - [j71]Jakob Engel, Vladlen Koltun, Daniel Cremers:
Direct Sparse Odometry. IEEE Trans. Pattern Anal. Mach. Intell. 40(3): 611-625 (2018) - [j70]Paul Bergmann, Rui Wang, Daniel Cremers:
Online Photometric Calibration of Auto Exposure Video for Realtime Visual Odometry and SLAM. IEEE Robotics Autom. Lett. 3(2): 627-634 (2018) - [j69]Nan Yang, Rui Wang, Xiang Gao, Daniel Cremers:
Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias, and Rolling Shutter Effect. IEEE Robotics Autom. Lett. 3(4): 2878-2885 (2018) - [j68]Hidenobu Matsuki, Lukas von Stumberg, Vladyslav Usenko, Jörg Stückler, Daniel Cremers:
Omnidirectional DSO: Direct Sparse Odometry With Fisheye Cameras. IEEE Robotics Autom. Lett. 3(4): 3693-3700 (2018) - [c254]Christiane Sommer, Daniel Cremers:
Joint Representation of Primitive and Non-primitive Objects for 3D Vision. 3DV 2018: 160-169 - [c253]Virginia Estellers, Frank R. Schmidt, Daniel Cremers:
Robust Fitting of Subdivision Surfaces for Smooth Shape Analysis. 3DV 2018: 277-285 - [c252]Vladyslav Usenko, Nikolaus Demmel, Daniel Cremers:
The Double Sphere Camera Model. 3DV 2018: 552-560 - [c251]Caner Hazirbas, Sebastian Georg Soyer, Maximilian Christian Staab, Laura Leal-Taixé, Daniel Cremers:
Deep Depth from Focus. ACCV (3) 2018: 525-541 - [c250]Thomas Möllenhoff, Zhenzhang Ye, Tao Wu, Daniel Cremers:
Combinatorial Preconditioners for Proximal Algorithms on Graphs. AISTATS 2018: 38-47 - [c249]Emanuel Laude, Tao Wu, Daniel Cremers:
A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization. AISTATS 2018: 491-499 - [c248]Patrick Wenzel, Qadeer Khan, Daniel Cremers, Laura Leal-Taixé:
Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs. CoRL 2018: 253-269 - [c247]Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff, Daniel Cremers:
Fight Ill-Posedness With Ill-Posedness: Single-Shot Variational Depth Super-Resolution From Shading. CVPR 2018: 164-174 - [c246]Roberto Henschel, Laura Leal-Taixé, Daniel Cremers, Bodo Rosenhahn:
Fusion of Head and Full-Body Detectors for Multi-Object Tracking. CVPR Workshops 2018: 1428-1437 - [c245]Emanuel Laude, Jan-Hendrik Lange, Jonas Schüpfer, Csaba Domokos, Laura Leal-Taixé, Frank R. Schmidt, Bjoern Andres, Daniel Cremers:
Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs. CVPR 2018: 1614-1624 - [c244]Philip Häusser, Johannes Plapp, Vladimir Golkov, Elie Aljalbout, Daniel Cremers:
Associative Deep Clustering: Training a Classification Network with No Labels. GCPR 2018: 18-32 - [c243]Csaba Domokos, Frank R. Schmidt, Daniel Cremers:
MRF Optimization with Separable Convex Prior on Partially Ordered Labels. ECCV (8) 2018: 341-356 - [c242]Zorah Lähner, Daniel Cremers, Tony Tung:
DeepWrinkles: Accurate and Realistic Clothing Modeling. ECCV (4) 2018: 698-715 - [c241]David Schubert, Nikolaus Demmel, Vladyslav Usenko, Jörg Stückler, Daniel Cremers:
Direct Sparse Odometry with Rolling Shutter. ECCV (8) 2018: 699-714 - [c240]Nan Yang, Rui Wang, Jörg Stückler, Daniel Cremers:
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry. ECCV (8) 2018: 835-852 - [c239]Thomas Frerix, Thomas Möllenhoff, Michael Möller, Daniel Cremers:
Proximal Backpropagation. ICLR (Poster) 2018 - [c238]Raluca Scona, Mariano Jaimez, Yvan R. Petillot, Maurice F. Fallon, Daniel Cremers:
StaticFusion: Background Reconstruction for Dense RGB-D SLAM in Dynamic Environments. ICRA 2018: 1-9 - [c237]Lukas von Stumberg, Vladyslav Usenko, Daniel Cremers:
Direct Sparse Visual-Inertial Odometry Using Dynamic Marginalization. ICRA 2018: 2510-2517 - [c236]David Schubert, Thore Goll, Nikolaus Demmel, Vladyslav Usenko, Jörg Stückler, Daniel Cremers:
The TUM VI Benchmark for Evaluating Visual-Inertial Odometry. IROS 2018: 1680-1687 - [c235]Xiang Gao, Rui Wang, Nikolaus Demmel, Daniel Cremers:
LDSO: Direct Sparse Odometry with Loop Closure. IROS 2018: 2198-2204 - [c234]Ioannis Chiotellis, Franziska Zimmermann, Daniel Cremers, Rudolph Triebel:
Incremental Semi-Supervised Learning from Streams for Object Classification. IROS 2018: 5743-5749 - [i74]Thomas Möllenhoff, Zhenzhang Ye, Tao Wu, Daniel Cremers:
Combinatorial Preconditioners for Proximal Algorithms on Graphs. CoRR abs/1801.05413 (2018) - [i73]Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox:
What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? CoRR abs/1801.06397 (2018) - [i72]Elie Aljalbout, Vladimir Golkov, Yawar Siddiqui, Daniel Cremers:
Clustering with Deep Learning: Taxonomy and New Methods. CoRR abs/1801.07648 (2018) - [i71]Lukas von Stumberg, Vladyslav Usenko, Daniel Cremers:
Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization. CoRR abs/1804.05625 (2018) - [i70]David Schubert, Thore Goll, Nikolaus Demmel, Vladyslav Usenko, Jörg Stückler, Daniel Cremers:
The TUM VI Benchmark for Evaluating Visual-Inertial Odometry. CoRR abs/1804.06120 (2018) - [i69]Seyed Hamid Rezatofighi, Roman Kaskman, Farbod T. Motlagh, Qinfeng Shi, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid:
Deep Perm-Set Net: Learn to predict sets with unknown permutation and cardinality using deep neural networks. CoRR abs/1805.00613 (2018) - [i68]Aleksei Vasilev, Vladimir Golkov, Ilona Lipp, Eleonora Sgarlata, Valentina Tomassini, Derek K. Jones, Daniel Cremers:
q-Space Novelty Detection with Variational Autoencoders. CoRR abs/1806.02997 (2018) - [i67]Marvin Eisenberger, Zorah Lähner, Daniel Cremers:
Divergence-Free Shape Interpolation and Correspondence. CoRR abs/1806.10417 (2018) - [i66]Patrick Wenzel, Qadeer Khan, Daniel Cremers, Laura Leal-Taixé:
Modular Vehicle Control for Transferring Semantic Information to Unseen Weather Conditions using GANs. CoRR abs/1807.01001 (2018) - [i65]Henning Tjaden, Ulrich Schwanecke, Elmar Schömer, Daniel Cremers:
A Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking. CoRR abs/1807.02087 (2018) - [i64]Nan Yang, Rui Wang, Jörg Stückler, Daniel Cremers:
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry. CoRR abs/1807.02570 (2018) - [i63]Vladyslav Usenko, Nikolaus Demmel, Daniel Cremers:
The Double Sphere Camera Model. CoRR abs/1807.08957 (2018) - [i62]David Schubert, Nikolaus Demmel, Vladyslav Usenko, Jörg Stückler, Daniel Cremers:
Direct Sparse Odometry with Rolling Shutter. CoRR abs/1808.00558 (2018) - [i61]Xiang Gao, Rui Wang, Nikolaus Demmel, Daniel Cremers:
LDSO: Direct Sparse Odometry with Loop Closure. CoRR abs/1808.01111 (2018) - [i60]Lingni Ma, Jörg Stückler, Tao Wu, Daniel Cremers:
Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform. CoRR abs/1808.01834 (2018) - [i59]Hidenobu Matsuki, Lukas von Stumberg, Vladyslav Usenko, Jörg Stückler, Daniel Cremers:
Omnidirectional DSO: Direct Sparse Odometry with Fisheye Cameras. CoRR abs/1808.02775 (2018) - [i58]Zorah Lähner, Daniel Cremers, Tony Tung:
DeepWrinkles: Accurate and Realistic Clothing Modeling. CoRR abs/1808.03417 (2018) - [i57]Bjoern Haefner, Songyou Peng, Alok Verma, Yvain Quéau, Daniel Cremers:
Photometric Depth Super-Resolution. CoRR abs/1809.10097 (2018) - 2017
- [j67]Luca Cosmo, Emanuele Rodolà, Andrea Albarelli, Facundo Mémoli, Daniel Cremers:
Consistent Partial Matching of Shape Collections via Sparse Modeling. Comput. Graph. Forum 36(1): 209-221 (2017) - [j66]Emanuele Rodolà, Luca Cosmo, Michael M. Bronstein, Andrea Torsello, Daniel Cremers:
Partial Functional Correspondence. Comput. Graph. Forum 36(1): 222-236 (2017) - [j65]Emanuele Rodolà, Michael Möller, Daniel Cremers:
Regularized Pointwise Map Recovery from Functional Correspondence. Comput. Graph. Forum 36(8): 700-711 (2017) - [j64]Daniel Cremers:
Computer Vision für 3-D-Rekonstruktion - Vom Nischenthema zum Mainstream. Inform. Spektrum 40(2): 205-209 (2017) - [j63]Youngwook Kee, Yegang Lee, Mohamed Souiai, Daniel Cremers, Junmo Kim:
Sequential Convex Programming for Computing Information-Theoretic Minimal Partitions: Nonconvex Nonsmooth Optimization. SIAM J. Imaging Sci. 10(4): 1845-1877 (2017) - [j62]Georg Kuschk, Pablo d'Angelo, David Gaudrie, Peter Reinartz, Daniel Cremers:
Spatially Regularized Fusion of Multiresolution Digital Surface Models. IEEE Trans. Geosci. Remote. Sens. 55(3): 1477-1488 (2017) - [c233]Matthias Vestner, Zorah Lähner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Daniel Cremers:
Efficient Deformable Shape Correspondence via Kernel Matching. 3DV 2017: 517-526 - [c232]Robert Maier, Raphael Schaller, Daniel Cremers:
Efficient Online Surface Correction for Real-time Large-Scale 3D Reconstruction. BMVC 2017 - [c231]Yvain Quéau, Tao Wu, François Lauze, Jean-Denis Durou, Daniel Cremers:
A Non-convex Variational Approach to Photometric Stereo under Inaccurate Lighting. CVPR 2017: 350-359 - [c230]Philip Häusser, Alexander Mordvintsev, Daniel Cremers:
Learning by Association - A Versatile Semi-Supervised Training Method for Neural Networks. CVPR 2017: 626-635 - [c229]Florian Bernard, Frank R. Schmidt, Johan Thunberg, Daniel Cremers:
A Combinatorial Solution to Non-Rigid 3D Shape-to-Image Matching. CVPR 2017: 1436-1445 - [c228]Mariano Jaimez, Thomas J. Cashman, Andrew W. Fitzgibbon, Javier González Jiménez, Daniel Cremers:
An Efficient Background Term for 3D Reconstruction and Tracking with Smooth Surface Models. CVPR 2017: 2575-2583 - [c227]Sergi Caelles, Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
One-Shot Video Object Segmentation. CVPR 2017: 5320-5329 - [c226]Miroslava Slavcheva, Maximilian Baust, Daniel Cremers, Slobodan Ilic:
KillingFusion: Non-rigid 3D Reconstruction without Correspondences. CVPR 2017: 5474-5483 - [c225]Matthias Vestner, Roee Litman, Emanuele Rodolà, Alexander M. Bronstein, Daniel Cremers:
Product Manifold Filter: Non-rigid Shape Correspondence via Kernel Density Estimation in the Product Space. CVPR 2017: 6681-6690 - [c224]Lukas von Stumberg, Vladyslav Usenko, Jakob Engel, Jörg Stückler, Daniel Cremers:
From monocular SLAM to autonomous drone exploration. ECMR 2017: 1-8 - [c223]Jonas Geiping, Hendrik Dirks, Daniel Cremers, Michael Möller:
Multiframe Motion Coupling for Video Super Resolution. EMMCVPR 2017: 123-138 - [c222]Yvain Quéau, Jean Mélou, Fabien Castan, Daniel Cremers, Jean-Denis Durou:
A Variational Approach to Shape-from-Shading Under Natural Illumination. EMMCVPR 2017: 342-357 - [c221]Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers:
Image-Based Localization Using LSTMs for Structured Feature Correlation. ICCV 2017: 627-637 - [c220]Thomas Möllenhoff, Daniel Cremers:
Sublabel-Accurate Discretization of Nonconvex Free-Discontinuity Problems. ICCV 2017: 1192-1200 - [c219]Tim Meinhardt, Michael Möller, Caner Hazirbas, Daniel Cremers:
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems. ICCV 2017: 1799-1808 - [c218]Philip Häusser, Thomas Frerix, Alexander Mordvintsev, Daniel Cremers:
Associative Domain Adaptation. ICCV 2017: 2784-2792 - [c217]Robert Maier, Kihwan Kim, Daniel Cremers, Jan Kautz, Matthias Nießner:
Intrinsic3D: High-Quality 3D Reconstruction by Joint Appearance and Geometry Optimization with Spatially-Varying Lighting. ICCV 2017: 3133-3141 - [c216]Rui Wang, Martin Schwörer, Daniel Cremers:
Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras. ICCV 2017: 3923-3931 - [c215]Songyou Peng, Bjoern Haefner, Yvain Quéau, Daniel Cremers:
Depth Super-Resolution Meets Uncalibrated Photometric Stereo. ICCV Workshops 2017: 2961-2968 - [c214]Maksym Dzitsiuk, Jürgen Sturm, Robert Maier, Lingni Ma, Daniel Cremers:
De-noising, stabilizing and completing 3D reconstructions on-the-go using plane priors. ICRA 2017: 3976-3983 - [c213]Mariano Jaimez, Christian Kerl, Javier González Jiménez, Daniel Cremers:
Fast odometry and scene flow from RGB-D cameras based on geometric clustering. ICRA 2017: 3992-3999 - [c212]Vladyslav Usenko, Lukas von Stumberg, Andrej Pangercic, Daniel Cremers:
Real-time trajectory replanning for MAVs using uniform B-splines and a 3D circular buffer. IROS 2017: 215-222 - [c211]Lingni Ma, Jörg Stückler, Christian Kerl, Daniel Cremers:
Multi-view deep learning for consistent semantic mapping with RGB-D cameras. IROS 2017: 598-605 - [c210]Georg Kuschk, Aljaz Bozic, Daniel Cremers:
Real-time variational stereo reconstruction with applications to large-scale dense SLAM. Intelligent Vehicles Symposium 2017: 1348-1355 - [c209]Daniel Bender, Wolfgang Koch, Daniel Cremers:
Map-based drone homing using shortcuts. MFI 2017: 505-511 - [c208]Daniel Cremers:
Direct methods for 3D reconstruction and visual SLAM. MVA 2017: 34-38 - [c207]Yvain Quéau, Matthieu Pizenberg, Jean-Denis Durou, Daniel Cremers:
Microgeometry capture and RGB albedo estimation by photometric stereo without demosaicing. QCAV 2017: 103380O - [c206]Martin Benning, Michael Möller, Raz Z. Nossek, Martin Burger, Daniel Cremers, Guy Gilboa, Carola-Bibiane Schönlieb:
Nonlinear Spectral Image Fusion. SSVM 2017: 41-53 - [c205]Yvain Quéau, Tao Wu, Daniel Cremers:
Semi-calibrated Near-Light Photometric Stereo. SSVM 2017: 656-668 - [c204]Jean Mélou, Yvain Quéau, Jean-Denis Durou, Fabien Castan, Daniel Cremers:
Beyond Multi-view Stereo: Shading-Reflectance Decomposition. SSVM 2017: 694-705 - [p8]Daniel Cremers:
Computer Vision für 3D Rekonstruktion. 50 Jahre Universitäts-Informatik in München 2017: 189-195 - [i56]Matthias Vestner, Roee Litman, Emanuele Rodolà, Alexander M. Bronstein, Daniel Cremers:
Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space. CoRR abs/1701.00669 (2017) - [i55]Vladyslav Usenko, Lukas von Stumberg, Andrej Pangercic, Daniel Cremers:
Real-Time Trajectory Replanning for MAVs using Uniform B-splines and 3D Circular Buffer. CoRR abs/1703.01416 (2017) - [i54]Martin Benning, Michael Möller, Raz Z. Nossek, Martin Burger, Daniel Cremers, Guy Gilboa, Carola-Bibiane Schönlieb:
Nonlinear Spectral Image Fusion. CoRR abs/1703.08001 (2017) - [i53]Lingni Ma, Jörg Stückler, Christian Kerl, Daniel Cremers:
Multi-View Deep Learning for Consistent Semantic Mapping with RGB-D Cameras. CoRR abs/1703.08866 (2017) - [i52]Yvain Quéau, Jean Mélou, Jean-Denis Durou, Daniel Cremers:
Dense Multi-view 3D-reconstruction Without Dense Correspondences. CoRR abs/1704.00337 (2017) - [i51]Caner Hazirbas, Laura Leal-Taixé, Daniel Cremers:
Deep Depth From Focus. CoRR abs/1704.01085 (2017) - [i50]Laura Leal-Taixé, Anton Milan, Konrad Schindler, Daniel Cremers, Ian D. Reid, Stefan Roth:
Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking. CoRR abs/1704.02781 (2017) - [i49]Tim Meinhardt, Michael Möller, Caner Hazirbas, Daniel Cremers:
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems. CoRR abs/1704.03488 (2017) - [i48]Vladimir Golkov, Marcin J. Skwark, Atanas Mirchev, Georgi Dikov, Alexander R. Geanes, Jeffrey L. Mendenhall, Jens Meiler, Daniel Cremers:
3D Deep Learning for Biological Function Prediction from Physical Fields. CoRR abs/1704.04039 (2017) - [i47]Nan Yang, Rui Wang, Daniel Cremers:
Feature-based or Direct: An Evaluation of Monocular Visual Odometry. CoRR abs/1705.04300 (2017) - [i46]Emanuel Laude, Jan-Hendrik Lange, Frank R. Schmidt, Bjoern Andres, Daniel Cremers:
Discrete-Continuous Splitting for Weakly Supervised Learning. CoRR abs/1705.05020 (2017) - [i45]Roberto Henschel, Laura Leal-Taixé, Daniel Cremers, Bodo Rosenhahn:
Improvements to Frank-Wolfe optimization for multi-detector multi-object tracking. CoRR abs/1705.08314 (2017) - [i44]Philip Häusser, Alexander Mordvintsev, Daniel Cremers:
Learning by Association - A versatile semi-supervised training method for neural networks. CoRR abs/1706.00909 (2017) - [i43]Thomas Frerix, Thomas Möllenhoff, Michael Möller, Daniel Cremers:
Proximal Backpropagation. CoRR abs/1706.04638 (2017) - [i42]Yvain Quéau, Bastien Durix, Tao Wu, Daniel Cremers, François Lauze, Jean-Denis Durou:
LED-based Photometric Stereo: Modeling, Calibration and Numerical Solution. CoRR abs/1707.01018 (2017) - [i41]Zorah Lähner, Matthias Vestner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Daniel Cremers:
Efficient Deformable Shape Correspondence via Kernel Matching. CoRR abs/1707.08991 (2017) - [i40]Songyou Peng, Bjoern Haefner, Yvain Quéau, Daniel Cremers:
Depth Super-Resolution Meets Uncalibrated Photometric Stereo. CoRR abs/1708.00411 (2017) - [i39]Philip Häusser, Thomas Frerix, Alexander Mordvintsev, Daniel Cremers:
Associative Domain Adaptation. CoRR abs/1708.00938 (2017) - [i38]Robert Maier, Kihwan Kim, Daniel Cremers, Jan Kautz, Matthias Nießner:
Intrinsic3D: High-Quality 3D Reconstruction by Joint Appearance and Geometry Optimization with Spatially-Varying Lighting. CoRR abs/1708.01670 (2017) - [i37]Rui Wang, Martin Schwörer, Daniel Cremers:
Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras. CoRR abs/1708.07878 (2017) - [i36]Robert Maier, Raphael Schaller, Daniel Cremers:
Efficient Online Surface Correction for Real-time Large-Scale 3D Reconstruction. CoRR abs/1709.03763 (2017) - [i35]Kevis-Kokitsi Maninis, Sergi Caelles, Yuhua Chen, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
Video Object Segmentation Without Temporal Information. CoRR abs/1709.06031 (2017) - [i34]Jean Mélou, Yvain Quéau, Jean-Denis Durou, Fabien Castan, Daniel Cremers:
Variational Reflectance Estimation from Multi-view Images. CoRR abs/1709.08378 (2017) - [i33]Yvain Quéau, Jean Mélou, Fabien Castan, Daniel Cremers, Jean-Denis Durou:
A Variational Approach to Shape-from-shading Under Natural Illumination. CoRR abs/1709.10354 (2017) - [i32]Paul Bergmann, Rui Wang, Daniel Cremers:
Online Photometric Calibration for Auto Exposure Video for Realtime Visual Odometry and SLAM. CoRR abs/1710.02081 (2017) - [i31]Jan Kukacka, Vladimir Golkov, Daniel Cremers:
Regularization for Deep Learning: A Taxonomy. CoRR abs/1710.10686 (2017) - [i30]Virginia Estellers, Frank R. Schmidt, Daniel Cremers:
Compression for Smooth Shape Analysis. CoRR abs/1711.10824 (2017) - [i29]Daniel Cremers, Laura Leal-Taixé, René Vidal:
Deep Learning for Computer Vision (Dagstuhl Seminar 17391). Dagstuhl Reports 7(9): 109-125 (2017) - 2016
- [j61]Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers:
Anisotropic Diffusion Descriptors. Comput. Graph. Forum 35(2): 431-441 (2016) - [j60]Or Litany, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers:
Non-Rigid Puzzles. Comput. Graph. Forum 35(5): 135-143 (2016) - [j59]Julia Diebold, Claudia Nieuwenhuis, Daniel Cremers:
Midrange Geometric Interactions for Semantic Segmentation - Constraints for Continuous Multi-label Optimization. Int. J. Comput. Vis. 117(3): 199-225 (2016) - [j58]Joan Duran, Michael Möller, Catalina Sbert, Daniel Cremers:
On the Implementation of Collaborative TV Regularization: Application to Cartoon+Texture Decomposition. Image Process. Line 6: 27-74 (2016) - [j57]Joan Duran, Michael Möller, Catalina Sbert, Daniel Cremers:
Collaborative Total Variation: A General Framework for Vectorial TV Models. SIAM J. Imaging Sci. 9(1): 116-151 (2016) - [j56]Martin Burger, Guy Gilboa, Michael Möller, Lina Eckardt, Daniel Cremers:
Spectral Decompositions Using One-Homogeneous Functionals. SIAM J. Imaging Sci. 9(3): 1374-1408 (2016) - [j55]Vladimir Golkov, Alexey Dosovitskiy, Jonathan I. Sperl, Marion I. Menzel, Michael Czisch, Philipp G. Sämann, Thomas Brox, Daniel Cremers:
q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI Scans. IEEE Trans. Medical Imaging 35(5): 1344-1351 (2016) - [c203]Luca Cosmo, Emanuele Rodolà, Michael M. Bronstein, Andrea Torsello, Daniel Cremers, Yusuf Sahillioglu:
Partial Matching of Deformable Shapes. 3DOR@Eurographics 2016 - [c202]Zorah Lähner, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers, Oliver Burghard, Luca Cosmo, Alexander Dieckmann, Reinhard Klein, Yusuf Sahillioglu:
Matching of Deformable Shapes with Topological Noise. 3DOR@Eurographics 2016 - [c201]Caner Hazirbas, Lingni Ma, Csaba Domokos, Daniel Cremers:
FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture. ACCV (1) 2016: 213-228 - [c200]Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers:
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching. CVPR 2016: 2185-2193 - [c199]Thomas Möllenhoff, Emanuel Laude, Michael Möller, Jan Lellmann, Daniel Cremers:
Sublabel-Accurate Relaxation of Nonconvex Energies. CVPR 2016: 3948-3956 - [c198]Nikolaus Mayer, Eddy Ilg, Philip Häusser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox:
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation. CVPR 2016: 4040-4048 - [c197]Ioannis Chiotellis, Rudolph Triebel, Thomas Windheuser, Daniel Cremers:
Non-rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding. ECCV (2) 2016: 327-342 - [c196]Emanuel Laude, Thomas Möllenhoff, Michael Möller, Jan Lellmann, Daniel Cremers:
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies. ECCV (1) 2016: 614-627 - [c195]Thomas Windheuser, Daniel Cremers:
A Convex Solution to Spatially-Regularized Correspondence Problems. ECCV (2) 2016: 853-868 - [c194]Daniel Bender, Fahmi Rouatbi, Marek Schikora, Daniel Cremers, Wolfgang Koch:
Scaling the world of monocular SLAM with INS-measurements for UAS navigation. FUSION 2016: 1493-1500 - [c193]Luca Cosmo, Andrea Albarelli, Filippo Bergamasco, Andrea Torsello, Emanuele Rodolà, Daniel Cremers:
A game-theoretical approach for joint matching of multiple feature throughout unordered images. ICPR 2016: 3715-3720 - [c192]Alexander Narr, Rudolph Triebel, Daniel Cremers:
Stream-based Active Learning for efficient and adaptive classification of 3D objects. ICRA 2016: 227-233 - [c191]Lingni Ma, Christian Kerl, Jörg Stückler, Daniel Cremers:
CPA-SLAM: Consistent plane-model alignment for direct RGB-D SLAM. ICRA 2016: 1285-1291 - [c190]Vladyslav Usenko, Jakob Engel, Jörg Stückler, Daniel Cremers:
Direct visual-inertial odometry with stereo cameras. ICRA 2016: 1885-1892 - [c189]Vladimir Golkov, Tim Sprenger, Jonathan Sperl, Marion I. Menzel, Michael Czisch, Philipp G. Sämann, Daniel Cremers:
Model-free novelty-based diffusion MRI. ISBI 2016: 1233-1236 - [c188]Daniel Bender, Daniel Cremers, Wolfgang Koch:
A position free boresight calibration for INS-camera systems. MFI 2016: 52-57 - [c187]Vladimir Golkov, Marcin J. Skwark, Antonij Golkov, Alexey Dosovitskiy, Thomas Brox, Jens Meiler, Daniel Cremers:
Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images. NIPS 2016: 4215-4223 - [p7]Matthias Vestner, Emanuele Rodolà, Thomas Windheuser, Samuel Rota Bulò, Daniel Cremers:
Applying Random Forests to the Problem of Dense Non-rigid Shape Correspondence. Perspectives in Shape Analysis 2016: 231-248 - [i28]Martin Burger, Guy Gilboa, Michael Möller, Lina Eckardt, Daniel Cremers:
Spectral Decompositions using One-Homogeneous Functionals. CoRR abs/1601.02912 (2016) - [i27]Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers:
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching. CoRR abs/1601.06070 (2016) - [i26]Emanuel Laude, Thomas Möllenhoff, Michael Möller, Jan Lellmann, Daniel Cremers:
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies. CoRR abs/1604.01980 (2016) - [i25]Jakob Engel, Vladyslav Usenko, Daniel Cremers:
A Photometrically Calibrated Benchmark For Monocular Visual Odometry. CoRR abs/1607.02555 (2016) - [i24]Jakob Engel, Vladlen Koltun, Daniel Cremers:
Direct Sparse Odometry. CoRR abs/1607.02565 (2016) - [i23]Matthias Vestner, Roee Litman, Alexander M. Bronstein, Emanuele Rodolà, Daniel Cremers:
Bayesian Inference of Bijective Non-Rigid Shape Correspondence. CoRR abs/1607.03425 (2016) - [i22]Lukas von Stumberg, Vladyslav Usenko, Jakob Engel, Jörg Stückler, Daniel Cremers:
Autonomous Exploration with a Low-Cost Quadrocopter using Semi-Dense Monocular SLAM. CoRR abs/1609.07835 (2016) - [i21]Maksym Dzitsiuk, Jürgen Sturm, Robert Maier, Lingni Ma, Daniel Cremers:
De-noising, Stabilizing and Completing 3D Reconstructions On-the-go using Plane Priors. CoRR abs/1609.08267 (2016) - [i20]Sergi Caelles, Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
One-Shot Video Object Segmentation. CoRR abs/1611.05198 (2016) - [i19]Florian Bernard, Frank R. Schmidt, Johan Thunberg, Daniel Cremers:
A Combinatorial Solution to Non-Rigid 3D Shape-to-Image Matching. CoRR abs/1611.05241 (2016) - [i18]Thomas Möllenhoff, Daniel Cremers:
Precise Relaxation of the Mumford-Shah Functional. CoRR abs/1611.06987 (2016) - [i17]Hendrik Dirks, Jonas Geiping, Daniel Cremers, Michael Möller:
Multiframe Motion Coupling via Infimal Convolution Regularization for Video Super Resolution. CoRR abs/1611.07767 (2016) - [i16]Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers:
Image-based Localization with Spatial LSTMs. CoRR abs/1611.07890 (2016) - [i15]Sahand Sharifzadeh, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks. CoRR abs/1612.03653 (2016) - 2015
- [j54]Maria Klodt, Katja Herzog, Reinhard Töpfer, Daniel Cremers:
Field phenotyping of grapevine growth using dense stereo reconstruction. BMC Bioinform. 16: 143:1-143:11 (2015) - [j53]Roberto Mecca, Emanuele Rodolà, Daniel Cremers:
Realistic photometric stereo using partial differential irradiance equation ratios. Comput. Graph. 51: 8-16 (2015) - [j52]Julia Diebold, Sibel Tari, Daniel Cremers:
The Role of Diffusion in Figure Hunt Games. J. Math. Imaging Vis. 52(1): 108-123 (2015) - [j51]Emanuele Rodolà, Andrea Albarelli, Daniel Cremers, Andrea Torsello:
A simple and effective relevance-based point sampling for 3D shapes. Pattern Recognit. Lett. 59: 41-47 (2015) - [j50]Thomas Möllenhoff, Evgeny Strekalovskiy, Michael Möller, Daniel Cremers:
The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings. SIAM J. Imaging Sci. 8(2): 827-857 (2015) - [j49]Youngwook Kee, Hansang Lee, Junho Yim, Daniel Cremers, Junmo Kim:
Entropy Minimization for Groupwise Planar Shape Co-alignment and its Applications. IEEE Signal Process. Lett. 22(11): 1922-1926 (2015) - [j48]Satish Madhogaria, Paul M. Baggenstoss, Marek Schikora, Wolfgang Koch, Daniel Cremers:
Car detection by fusion of HOG and causal MRF. IEEE Trans. Aerosp. Electron. Syst. 51(1): 575-590 (2015) - [j47]Michael Möller, Martin Benning, Carola Schönlieb, Daniel Cremers:
Variational Depth From Focus Reconstruction. IEEE Trans. Image Process. 24(12): 5369-5378 (2015) - [c186]Mariano Jaimez, Mohamed Souiai, Jörg Stückler, Javier González Jiménez, Daniel Cremers:
Motion Cooperation: Smooth Piece-wise Rigid Scene Flow from RGB-D Images. 3DV 2015: 64-72 - [c185]Robert Maier, Jörg Stückler, Daniel Cremers:
Super-resolution Keyframe Fusion for 3D Modeling with High-Quality Textures. 3DV 2015: 536-544 - [c184]Vladyslav Usenko, Jakob Engel, Jörg Stückler, Daniel Cremers:
Reconstructing Street-Scenes in Real-Time from a Driving Car. 3DV 2015: 607-614 - [c183]Filippo Bergamasco, Andrea Albarelli, Luca Cosmo, Andrea Torsello, Emanuele Rodolà, Daniel Cremers:
Adopting an unconstrained ray model in light-field cameras for 3D shape reconstruction. CVPR 2015: 3003-3012 - [c182]Rudolph Triebel, Kai Oliver Arras, Rachid Alami, Lucas Beyer, Stefan Breuers, Raja Chatila, Mohamed Chetouani, Daniel Cremers, Vanessa Evers, Michelangelo Fiore, Hayley Hung, Omar A. Islas Ramírez, Michiel Joosse, Harmish Khambhaita, Tomasz Kucner, Bastian Leibe, Achim J. Lilienthal, Timm Linder, Manja Lohse, Martin Magnusson, Billy Okal, Luigi Palmieri, Umer Rafi, Marieke van Rooij, Lu Zhang:
SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports. FSR 2015: 607-622 - [c181]Michael Möller, Julia Diebold, Guy Gilboa, Daniel Cremers:
Learning Nonlinear Spectral Filters for Color Image Reconstruction. ICCV 2015: 289-297 - [c180]Mohamed Souiai, Martin R. Oswald, Youngwook Kee, Junmo Kim, Marc Pollefeys, Daniel Cremers:
Entropy Minimization for Convex Relaxation Approaches. ICCV 2015: 1778-1786 - [c179]Christian Kerl, Jörg Stückler, Daniel Cremers:
Dense Continuous-Time Tracking and Mapping with Rolling Shutter RGB-D Cameras. ICCV 2015: 2264-2272 - [c178]Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox:
FlowNet: Learning Optical Flow with Convolutional Networks. ICCV 2015: 2758-2766 - [c177]Jan Stühmer, Sebastian Nowozin, Andrew W. Fitzgibbon, Richard Szeliski, Travis Perry, Sunil Acharya, Daniel Cremers, Jamie Shotton:
Model-Based Tracking at 300Hz Using Raw Time-of-Flight Observations. ICCV 2015: 3577-3585 - [c176]Mariano Jaimez, Mohamed Souiai, Javier González Jiménez, Daniel Cremers:
A primal-dual framework for real-time dense RGB-D scene flow. ICRA 2015: 98-104 - [c175]Dennis Mund, Rudolph Triebel, Daniel Cremers:
Active online confidence boosting for efficient object classification. ICRA 2015: 1367-1373 - [c174]David Caruso, Jakob Engel, Daniel Cremers:
Large-scale direct SLAM for omnidirectional cameras. IROS 2015: 141-148 - [c173]Jakob Engel, Jörg Stückler, Daniel Cremers:
Large-scale direct SLAM with stereo cameras. IROS 2015: 1935-1942 - [c172]Ye Tao, Rudolph Triebel, Daniel Cremers:
Semi-supervised online learning for efficient classification of objects in 3D data streams. IROS 2015: 2904-2910 - [c171]Vladimir Golkov, Alexey Dosovitskiy, Philipp G. Sämann, Jonathan I. Sperl, Tim Sprenger, Michael Czisch, Marion I. Menzel, Pedro A. Gómez, Axel Haase, Thomas Brox, Daniel Cremers:
q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans. MICCAI (1) 2015: 37-44 - [c170]Caner Hazirbas, Julia Diebold, Daniel Cremers:
Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation. SSVM 2015: 243-255 - [c169]Julia Diebold, Nikolaus Demmel, Caner Hazirbas, Michael Möller, Daniel Cremers:
Interactive Multi-label Segmentation of RGB-D Images. SSVM 2015: 294-306 - [c168]Emanuele Rodolà, Michael Möller, Daniel Cremers:
Point-wise Map Recovery and Refinement from Functional Correspondence. VMV 2015: 25-32 - [e11]Daniel Cremers, Ian D. Reid, Hideo Saito, Ming-Hsuan Yang:
Computer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part I. Lecture Notes in Computer Science 9003, Springer 2015, ISBN 978-3-319-16864-7 [contents] - [e10]Daniel Cremers, Ian D. Reid, Hideo Saito, Ming-Hsuan Yang:
Computer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part II. Lecture Notes in Computer Science 9004, Springer 2015, ISBN 978-3-319-16807-4 [contents] - [e9]Daniel Cremers, Ian D. Reid, Hideo Saito, Ming-Hsuan Yang:
Computer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part III. Lecture Notes in Computer Science 9005, Springer 2015, ISBN 978-3-319-16810-4 [contents] - [e8]Daniel Cremers, Ian D. Reid, Hideo Saito, Ming-Hsuan Yang:
Computer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part IV. Lecture Notes in Computer Science 9006, Springer 2015, ISBN 978-3-319-16816-6 [contents] - [e7]Daniel Cremers, Ian D. Reid, Hideo Saito, Ming-Hsuan Yang:
Computer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part V. Lecture Notes in Computer Science 9007, Springer 2015, ISBN 978-3-319-16813-5 [contents] - [r1]Daniel Cremers:
Image Segmentation with Shape Priors: Explicit Versus Implicit Representations. Handbook of Mathematical Methods in Imaging 2015: 1909-1944 - [i14]Philipp Fischer, Alexey Dosovitskiy, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox:
FlowNet: Learning Optical Flow with Convolutional Networks. CoRR abs/1504.06852 (2015) - [i13]Emanuele Rodolà, Luca Cosmo, Michael M. Bronstein, Andrea Torsello, Daniel Cremers:
Partial Functional Correspondence. CoRR abs/1506.05274 (2015) - [i12]Emanuele Rodolà, Michael Möller, Daniel Cremers:
Point-wise Map Recovery and Refinement from Functional Correspondence. CoRR abs/1506.05603 (2015) - [i11]Joan Duran, Michael Möller, Catalina Sbert, Daniel Cremers:
Collaborative Total Variation: A General Framework for Vectorial TV Models. CoRR abs/1508.01308 (2015) - [i10]Thomas Möllenhoff, Emanuel Laude, Michael Möller, Jan Lellmann, Daniel Cremers:
Sublabel-Accurate Relaxation of Nonconvex Energies. CoRR abs/1512.01383 (2015) - [i9]Nikolaus Mayer, Eddy Ilg, Philip Häusser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox:
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation. CoRR abs/1512.02134 (2015) - 2014
- [j46]Emanuele Rodolà, Samuel Rota Bulò, Daniel Cremers:
Robust Region Detection via Consensus Segmentation of Deformable Shapes. Comput. Graph. Forum 33(5): 97-106 (2014) - [j45]Bastian Goldlücke, Mathieu Aubry, Kalin Kolev, Daniel Cremers:
A Super-Resolution Framework for High-Accuracy Multiview Reconstruction. Int. J. Comput. Vis. 106(2): 172-191 (2014) - [j44]Zicheng Liu, Michael Beetz, Daniel Cremers, Jürgen Gall, Wanqing Li, Dejan Pangercic, Jürgen Sturm, Yu-Wing Tai:
Introduction to the special issue on visual understanding and applications with RGB-D cameras. J. Vis. Commun. Image Represent. 25(1): 1 (2014) - [j43]Jakob Engel, Jürgen Sturm, Daniel Cremers:
Scale-aware navigation of a low-cost quadrocopter with a monocular camera. Robotics Auton. Syst. 62(11): 1646-1656 (2014) - [j42]Evgeny Strekalovskiy, Antonin Chambolle, Daniel Cremers:
Convex Relaxation of Vectorial Problems with Coupled Regularization. SIAM J. Imaging Sci. 7(1): 294-336 (2014) - [j41]Marek Schikora, Amadou Gning, Lyudmila Mihaylova, Daniel Cremers, Wolfgang Koch:
Box-particle probability hypothesis density filtering. IEEE Trans. Aerosp. Electron. Syst. 50(3): 1660-1672 (2014) - [j40]Felix Endres, Jürgen Hess, Jürgen Sturm, Daniel Cremers, Wolfram Burgard:
3-D Mapping With an RGB-D Camera. IEEE Trans. Robotics 30(1): 177-187 (2014) - [c167]Christian Kerl, Mohamed Souiai, Jürgen Sturm, Daniel Cremers:
Towards Illumination-Invariant 3D Reconstruction Using ToF RGB-D Cameras. 3DV 2014: 39-46 - [c166]Asako Kanezaki, Emanuele Rodolà, Daniel Cremers, Tatsuya Harada:
Learning Similarities for Rigid and Non-rigid Object Detection. 3DV 2014: 720-727 - [c165]Martin R. Oswald, Daniel Cremers:
Surface Normal Integration for Convex Space-time Multi-view Reconstruction. BMVC 2014 - [c164]Thomas Windheuser, Matthias Vestner, Emanuele Rodolà, Rudolph Triebel, Daniel Cremers:
Optimal Intrinsic Descriptors for Non-Rigid Shape Analysis. BMVC 2014 - [c163]Youngwook Kee, Mohamed Souiai, Daniel Cremers, Junmo Kim:
Sequential Convex Relaxation for Mutual Information-Based Unsupervised Figure-Ground Segmentation. CVPR 2014: 4082-4089 - [c162]Emanuele Rodolà, Samuel Rota Bulò, Thomas Windheuser, Matthias Vestner, Daniel Cremers:
Dense Non-rigid Shape Correspondence Using Random Forests. CVPR 2014: 4177-4184 - [c161]Robert Maier, Jürgen Sturm, Daniel Cremers:
Submap-Based Bundle Adjustment for 3D Reconstruction from RGB-D Data. GCPR 2014: 54-65 - [c160]Michael Strobel, Julia Diebold, Daniel Cremers:
Flow and Color Inpainting for Video Completion. GCPR 2014: 293-304 - [c159]Tobias Gurdan, Martin R. Oswald, Daniel Gurdan, Daniel Cremers:
Spatial and Temporal Interpolation of Multi-view Image Sequences. GCPR 2014: 305-316 - [c158]Rudolph Triebel, Jan Stühmer, Mohamed Souiai, Daniel Cremers:
Active Online Learning for Interactive Segmentation Using Sparse Gaussian Processes. GCPR 2014: 641-652 - [c157]Martin Ralf Oswald, Jan Stühmer, Daniel Cremers:
Generalized Connectivity Constraints for Spatio-temporal 3D Reconstruction. ECCV (4) 2014: 32-46 - [c156]Evgeny Strekalovskiy, Daniel Cremers:
Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional. ECCV (2) 2014: 127-141 - [c155]Maria Klodt, Daniel Cremers:
High-Resolution Plant Shape Measurements from Multi-view Stereo Reconstruction. ECCV Workshops (4) 2014: 174-184 - [c154]Claudia Nieuwenhuis, Simon Hawe, Martin Kleinsteuber, Daniel Cremers:
Co-Sparse Textural Similarity for Interactive Segmentation. ECCV (6) 2014: 285-301 - [c153]Mathieu Andreux, Emanuele Rodolà, Mathieu Aubry, Daniel Cremers:
Anisotropic Laplace-Beltrami Operators for Shape Analysis. ECCV Workshops (4) 2014: 299-312 - [c152]Jakob Engel, Thomas Schöps, Daniel Cremers:
LSD-SLAM: Large-Scale Direct Monocular SLAM. ECCV (2) 2014: 834-849 - [c151]Thomas Möllenhoff, Evgeny Strekalovskiy, Michael Möller, Daniel Cremers:
Low Rank Priors for Color Image Regularization. EMMCVPR 2014: 126-140 - [c150]Joan Duran, Michael Möller, Catalina Sbert, Daniel Cremers:
A Novel Framework for Nonlocal Vectorial Total Variation Based on ℓ p, q, r -norms. EMMCVPR 2014: 141-154 - [c149]Jan Stühmer, Daniel Cremers:
A Fast Projection Method for Connectivity Constraints in Image Segmentation. EMMCVPR 2014: 183-196 - [c148]David Weikersdorfer, David B. Adrian, Daniel Cremers, Jörg Conradt:
Event-based 3D SLAM with a depth-augmented dynamic vision sensor. ICRA 2014: 359-364 - [c147]Frank Steinbrücker, Jürgen Sturm, Daniel Cremers:
Volumetric 3D mapping in real-time on a CPU. ICRA 2014: 2021-2028 - [c146]H. Alvarez, Lina María Paz, Jürgen Sturm, Daniel Cremers:
Collision Avoidance for Quadrotors with a Monocular Camera. ISER 2014: 195-209 - [c145]Thomas Schöps, Jakob Engel, Daniel Cremers:
Semi-dense visual odometry for AR on a smartphone. ISMAR 2014: 145-150 - [c144]Shoubhik Debnath, Shiv Sankar Baishya, Rudolph Triebel, Varun Dutt, Daniel Cremers:
Environment-Adaptive Learning: How Clustering Helps to Obtain Good Training Data. KI 2014: 68-79 - [i8]Thomas Möllenhoff, Evgeny Strekalovskiy, Michael Möller, Daniel Cremers:
The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings. CoRR abs/1407.1723 (2014) - [i7]Michael Möller, Martin Benning, Carola-Bibiane Schönlieb, Daniel Cremers:
Variational Depth from Focus Reconstruction. CoRR abs/1408.0173 (2014) - 2013
- [j39]Claudia Nieuwenhuis, Eno Töppe, Daniel Cremers:
A Survey and Comparison of Discrete and Continuous Multi-label Optimization Approaches for the Potts Model. Int. J. Comput. Vis. 104(3): 223-240 (2013) - [j38]Daniel Cremers, Evgeny Strekalovskiy:
Total Cyclic Variation and Generalizations. J. Math. Imaging Vis. 47(3): 258-277 (2013) - [j37]Claudia Nieuwenhuis, Daniel Cremers:
Spatially Varying Color Distributions for Interactive Multilabel Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 35(5): 1234-1247 (2013) - [j36]Bastian Goldluecke, Evgeny Strekalovskiy, Daniel Cremers:
Tight Convex Relaxations for Vector-Valued Labeling. SIAM J. Imaging Sci. 6(3): 1626-1664 (2013) - [c143]Emanuele Rodolà, Tatsuya Harada, Yasuo Kuniyoshi, Daniel Cremers:
Efficient Shape Matching using Vector Extrapolation. BMVC 2013 - [c142]Eno Töppe, Claudia Nieuwenhuis, Daniel Cremers:
Relative Volume Constraints for Single View 3D Reconstruction. CVPR 2013: 177-184 - [c141]Maria Klodt, Jürgen Sturm, Daniel Cremers:
Scale-Aware Object Tracking with Convex Shape Constraints on RGB-D Images. GCPR 2013: 111-120 - [c140]Franz Stangl, Mohamed Souiai, Daniel Cremers:
Performance Evaluation of Narrow Band Methods for Variational Stereo Reconstruction. GCPR 2013: 194-204 - [c139]Jürgen Sturm, Erik Bylow, Fredrik Kahl, Daniel Cremers:
CopyMe3D: Scanning and Printing Persons in 3D. GCPR 2013: 405-414 - [c138]Thomas Möllenhoff, Claudia Nieuwenhuis, Eno Töppe, Daniel Cremers:
Efficient Convex Optimization for Minimal Partition Problems with Volume Constraints. EMMCVPR 2013: 94-107 - [c137]Mohamed Souiai, Evgeny Strekalovskiy, Claudia Nieuwenhuis, Daniel Cremers:
A Co-occurrence Prior for Continuous Multi-label Optimization. EMMCVPR 2013: 209-222 - [c136]Emanuele Rodolà, Andrea Torsello, Tatsuya Harada, Yasuo Kuniyoshi, Daniel Cremers:
Elastic Net Constraints for Shape Matching. ICCV 2013: 1169-1176 - [c135]Jakob Engel, Jürgen Sturm, Daniel Cremers:
Semi-dense Visual Odometry for a Monocular Camera. ICCV 2013: 1449-1456 - [c134]Claudia Nieuwenhuis, Evgeny Strekalovskiy, Daniel Cremers:
Proportion Priors for Image Sequence Segmentation. ICCV 2013: 2328-2335 - [c133]Jan Stühmer, Peter Schröder, Daniel Cremers:
Tree Shape Priors with Connectivity Constraints Using Convex Relaxation on General Graphs. ICCV 2013: 2336-2343 - [c132]Jan Lellmann, Evgeny Strekalovskiy, Sabrina Koetter, Daniel Cremers:
Total Variation Regularization for Functions with Values in a Manifold. ICCV 2013: 2944-2951 - [c131]Frank Steinbrücker, Christian Kerl, Daniel Cremers:
Large-Scale Multi-resolution Surface Reconstruction from RGB-D Sequences. ICCV 2013: 3264-3271 - [c130]Mohamed Souiai, Claudia Nieuwenhuis, Evgeny Strekalovskiy, Daniel Cremers:
Convex Optimization for Scene Understanding. ICCV Workshops 2013: 9-14 - [c129]Julia Bergbauer, Claudia Nieuwenhuis, Mohamed Souiai, Daniel Cremers:
Proximity Priors for Variational Semantic Segmentation and Recognition. ICCV Workshops 2013: 15-21 - [c128]Martin R. Oswald, Daniel Cremers:
A Convex Relaxation Approach to Space Time Multi-view 3D Reconstruction. ICCV Workshops 2013: 291-298 - [c127]Georg Kuschk, Daniel Cremers:
Fast and Accurate Large-Scale Stereo Reconstruction Using Variational Methods. ICCV Workshops 2013: 700-707 - [c126]David Weikersdorfer, Alexander Schick, Daniel Cremers:
Depth-adaptive supervoxels for RGB-D video segmentation. ICIP 2013: 2708-2712 - [c125]Christian Kerl, Jürgen Sturm, Daniel Cremers:
Robust odometry estimation for RGB-D cameras. ICRA 2013: 3748-3754 - [c124]Tayyab Naseer, Jürgen Sturm, Daniel Cremers:
FollowMe: Person following and gesture recognition with a quadrocopter. IROS 2013: 624-630 - [c123]Christian Kerl, Jürgen Sturm, Daniel Cremers:
Dense visual SLAM for RGB-D cameras. IROS 2013: 2100-2106 - [c122]Erik Bylow, Jürgen Sturm, Christian Kerl, Fredrik Kahl, Daniel Cremers:
Real-Time Camera Tracking and 3D Reconstruction Using Signed Distance Functions. Robotics: Science and Systems 2013 - [p6]Martin R. Oswald, Eno Töppe, Claudia Nieuwenhuis, Daniel Cremers:
A Review of Geometry Recovery from a Single Image Focusing on Curved Object Reconstruction. Innovations for Shape Analysis, Models and Algorithms 2013: 343-378 - [p5]Daniel Cremers:
Shape Priors for Image Segmentation. Shape Perception in Human and Computer Vision 2013: 103-117 - [p4]Maria Klodt, Frank Steinbrücker, Daniel Cremers:
Moment Constraints in Convex Optimization for Segmentation and Tracking. Advanced Topics in Computer Vision 2013: 215-242 - [i6]Claudia Nieuwenhuis, Daniel Cremers, Simon Hawe, Martin Kleinsteuber:
Co-Sparse Textural Similarity for Image Segmentation. CoRR abs/1312.4746 (2013) - 2012
- [j35]Frank Steinbrücker, Anke Meyer-Baese, Thomas Schlossbauer, Daniel Cremers:
Evaluation of a Nonrigid Motion Compensation Technique Based on Spatiotemporal Features for Small Lesion Detection in Breast MRI. Adv. Artif. Neural Syst. 2012: 808602:1-808602:10 (2012) - [j34]Marek Schikora, Balram Neupane, Satish Madhogaria, Wolfgang Koch, Daniel Cremers, Heribert Hirt, Karl-Heinz Kogel, Adam Schikora:
An image classification approach to analyze the suppression of plant immunity by the human pathogen Salmonella Typhimurium. BMC Bioinform. 13: 171 (2012) - [j33]Thomas Schoenemann, Fredrik Kahl, Simon Masnou, Daniel Cremers:
A Linear Framework for Region-Based Image Segmentation and Inpainting Involving Curvature Penalization. Int. J. Comput. Vis. 99(1): 53-68 (2012) - [j32]Daniel Cremers:
Optimal solutions for semantic image decomposition. Image Vis. Comput. 30(8): 476-477 (2012) - [j31]Siqi Chen, Daniel Cremers, Richard J. Radke:
Image segmentation with one shape prior - A template-based formulation. Image Vis. Comput. 30(12): 1032-1042 (2012) - [j30]Kalin Kolev, Thomas Brox, Daniel Cremers:
Fast Joint Estimation of Silhouettes and Dense 3D Geometry from Multiple Images. IEEE Trans. Pattern Anal. Mach. Intell. 34(3): 493-505 (2012) - [j29]Bastian Goldlücke, Evgeny Strekalovskiy, Daniel Cremers:
The Natural Vectorial Total Variation Which Arises from Geometric Measure Theory. SIAM J. Imaging Sci. 5(2): 537-563 (2012) - [j28]Antonin Chambolle, Daniel Cremers, Thomas Pock:
A Convex Approach to Minimal Partitions. SIAM J. Imaging Sci. 5(4): 1113-1158 (2012) - [j27]Thomas Schoenemann, Daniel Cremers:
A Coding-Cost Framework for Super-Resolution Motion Layer Decomposition. IEEE Trans. Image Process. 21(3): 1097-1110 (2012) - [c121]Martin R. Oswald, Eno Töppe, Daniel Cremers:
Fast and globally optimal single view reconstruction of curved objects. CVPR 2012: 534-541 - [c120]Evgeny Strekalovskiy, Antonin Chambolle, Daniel Cremers:
A convex representation for the vectorial Mumford-Shah functional. CVPR 2012: 1712-1719 - [c119]Youngwook Kee, Daniel Cremers, Junmo Kim:
Groupwise Shape Registration Based on Entropy Minimization. DAGM/OAGM Symposium 2012: 347-356 - [c118]Evgeny Strekalovskiy, Claudia Nieuwenhuis, Daniel Cremers:
Nonmetric Priors for Continuous Multilabel Optimization. ECCV (7) 2012: 208-221 - [c117]Thomas Windheuser, Hiroshi Ishikawa, Daniel Cremers:
Generalized Roof Duality for Multi-Label Optimization: Optimal Lower Bounds and Persistency. ECCV (6) 2012: 400-413 - [c116]Nikolai Ufer, Mohamed Souiai, Daniel Cremers:
Wehrli 2.0: An Algorithm for "Tidying up Art". ECCV Workshops (1) 2012: 532-541 - [c115]Marek Schikora, Amadou Gning, Lyudmila Mihaylova, Daniel Cremers, Wolfgang Koch:
Box-particle PHD filter for multi-target tracking. FUSION 2012: 106-113 - [c114]Felix Endres, Jürgen Hess, Nikolas Engelhard, Jürgen Sturm, Daniel Cremers, Wolfram Burgard:
An evaluation of the RGB-D SLAM system. ICRA 2012: 1691-1696 - [c113]Thomas Rühr, Jürgen Sturm, Dejan Pangercic, Michael Beetz, Daniel Cremers:
A generalized framework for opening doors and drawers in kitchen environments. ICRA 2012: 3852-3858 - [c112]Jürgen Sturm, Nikolas Engelhard, Felix Endres, Wolfram Burgard, Daniel Cremers:
A benchmark for the evaluation of RGB-D SLAM systems. IROS 2012: 573-580 - [c111]Licong Zhang, Jürgen Sturm, Daniel Cremers, Dongheui Lee:
Real-time human motion tracking using multiple depth cameras. IROS 2012: 2389-2395 - [c110]Jakob Engel, Jürgen Sturm, Daniel Cremers:
Camera-based navigation of a low-cost quadrocopter. IROS 2012: 2815-2821 - 2011
- [b2]Andreas Wedel, Daniel Cremers:
Stereo Scene Flow for 3D Motion Analysis. Springer 2011, ISBN 978-0-85729-964-2, pp. I-IX, 1-128 - [j26]Thomas Windheuser, Ulrich Schlickewei, Frank R. Schmidt, Daniel Cremers:
Large-Scale Integer Linear Programming for Orientation Preserving 3D Shape Matching. Comput. Graph. Forum 30(5): 1471-1480 (2011) - [j25]Andreas Wedel, Thomas Brox, Tobi Vaudrey, Clemens Rabe, Uwe Franke, Daniel Cremers:
Stereoscopic Scene Flow Computation for 3D Motion Understanding. Int. J. Comput. Vis. 95(1): 29-51 (2011) - [j24]Daniel Cremers, Kalin Kolev:
Multiview Stereo and Silhouette Consistency via Convex Functionals over Convex Domains. IEEE Trans. Pattern Anal. Mach. Intell. 33(6): 1161-1174 (2011) - [j23]Anita Sellent, Martin Eisemann, Bastian Goldlücke, Daniel Cremers, Marcus A. Magnor:
Motion Field Estimation from Alternate Exposure Images. IEEE Trans. Pattern Anal. Mach. Intell. 33(8): 1577-1589 (2011) - [j22]Kalin Kolev, Norbert Kirchgeßner, Sebastian Houben, Agnes Csiszár, Wolfgang Rubner, Christoph Palm, Björn Eiben, Rudolf Merkel, Daniel Cremers:
A variational approach to vesicle membrane reconstruction from fluorescence imaging. Pattern Recognit. 44(12): 2944-2958 (2011) - [j21]Thomas Schoenemann, Simon Masnou, Daniel Cremers:
The Elastic Ratio: Introducing Curvature Into Ratio-Based Image Segmentation. IEEE Trans. Image Process. 20(9): 2565-2581 (2011) - [c109]Marek Schikora, Marc Oispuu, Wolfgang Koch, Daniel Cremers:
Multiple source localization based on biased bearings using the intensity filter - approach and experimental results. CAMSAP 2011: 61-64 - [c108]Evgeny Strekalovskiy, Daniel Cremers:
Total variation for cyclic structures: Convex relaxation and efficient minimization. CVPR 2011: 1905-1911 - [c107]Mathieu Aubry, Ulrich Schlickewei, Daniel Cremers:
Pose-Consistent 3D Shape Segmentation Based on a Quantum Mechanical Feature Descriptor. DAGM-Symposium 2011: 122-131 - [c106]Frank R. Schmidt, Thomas Windheuser, Ulrich Schlickewei, Daniel Cremers:
Dense Elastic 3D Shape Matching. Efficient Algorithms for Global Optimization Methods in Computer Vision 2011: 1-18 - [c105]Claudia Nieuwenhuis, Eno Töppe, Daniel Cremers:
Space-Varying Color Distributions for Interactive Multiregion Segmentation: Discrete versus Continuous Approaches. EMMCVPR 2011: 177-190 - [c104]Marek Schikora, Wolfgang Koch, Roy L. Streit, Daniel Cremers:
Sequential Monte Carlo method for the iFilter. FUSION 2011: 1-8 - [c103]Satish Madhogaria, Marek Schikora, Wolfgang Koch, Daniel Cremers:
Pixel-based classification method for detecting unhealthy regions in leaf images. GI-Jahrestagung 2011: 482 - [c102]Marek Schikora, Wolfgang Koch, Daniel Cremers:
Multi-object tracking via high accuracy optical flowand finite set statistics. ICASSP 2011: 1409-1412 - [c101]Bastian Goldlücke, Daniel Cremers:
Introducing total curvature for image processing. ICCV 2011: 1267-1274 - [c100]Mathieu Aubry, Kalin Kolev, Bastian Goldlücke, Daniel Cremers:
Decoupling photometry and geometry in dense variational camera calibration. ICCV 2011: 1411-1418 - [c99]Thomas Windheuser, Ulrich Schlickewei, Frank R. Schmidt, Daniel Cremers:
Geometrically consistent elastic matching of 3D shapes: A linear programming solution. ICCV 2011: 2134-2141 - [c98]Maria Klodt, Daniel Cremers:
A convex framework for image segmentation with moment constraints. ICCV 2011: 2236-2243 - [c97]Evgeny Strekalovskiy, Bastian Goldlücke, Daniel Cremers:
Tight convex relaxations for vector-valued labeling problems. ICCV 2011: 2328-2335 - [c96]Evgeny Strekalovskiy, Daniel Cremers:
Generalized ordering constraints for multilabel optimization. ICCV 2011: 2619-2626 - [c95]Frank Steinbrücker, Jürgen Sturm, Daniel Cremers:
Real-time visual odometry from dense RGB-D images. ICCV Workshops 2011: 719-722 - [c94]Mathieu Aubry, Ulrich Schlickewei, Daniel Cremers:
The wave kernel signature: A quantum mechanical approach to shape analysis. ICCV Workshops 2011: 1626-1633 - [e6]Daniel Cremers, Marcus A. Magnor, Martin R. Oswald, Lihi Zelnik-Manor:
Video Processing and Computational Video - International Seminar, Dagstuhl Castle, Germany, October 10-15, 2010. Revised Papers. Lecture Notes in Computer Science 7082, Springer 2011, ISBN 978-3-642-24869-6 [contents] - [i5]Thomas Schoenemann, Simon Masnou, Daniel Cremers:
On a linear programming approach to the discrete Willmore boundary value problem and generalizations. CoRR abs/1101.0777 (2011) - [i4]Thomas Schoenemann, Fredrik Kahl, Simon Masnou, Daniel Cremers:
A linear framework for region-based image segmentation and inpainting involving curvature penalization. CoRR abs/1102.3830 (2011) - 2010
- [j20]Thomas Brox, Bodo Rosenhahn, Juergen Gall, Daniel Cremers:
Combined Region and Motion-Based 3D Tracking of Rigid and Articulated Objects. IEEE Trans. Pattern Anal. Mach. Intell. 32(3): 402-415 (2010) - [j19]Thomas Schoenemann, Daniel Cremers:
A Combinatorial Solution for Model-Based Image Segmentation and Real-Time Tracking. IEEE Trans. Pattern Anal. Mach. Intell. 32(7): 1153-1164 (2010) - [j18]Thomas Pock, Daniel Cremers, Horst Bischof, Antonin Chambolle:
Global Solutions of Variational Models with Convex Regularization. SIAM J. Imaging Sci. 3(4): 1122-1145 (2010) - [c93]Eno Töppe, Martin R. Oswald, Daniel Cremers, Carsten Rother:
Image-Based 3D Modeling via Cheeger Sets. ACCV (1) 2010: 53-64 - [c92]Thomas Schoenemann, Simon Masnou, Daniel Cremers:
On a Linear Programming Approach to the Discrete Willmore Boundary Value Problem and Generalizations. Curves and Surfaces 2010: 629-646 - [c91]Bastian Goldlücke, Daniel Cremers:
An approach to vectorial total variation based on geometric measure theory. CVPR 2010: 327-333 - [c90]Jan Stühmer, Stefan Gumhold, Daniel Cremers:
Real-Time Dense Geometry from a Handheld Camera. DAGM-Symposium 2010: 11-20 - [c89]Claudia Nieuwenhuis, Benjamin Berkels, Martin Rumpf, Daniel Cremers:
Interactive Motion Segmentation. DAGM-Symposium 2010: 483-492 - [c88]Eno Töppe, Martin R. Oswald, Daniel Cremers, Carsten Rother:
Silhouette-Based Variational Methods for Single View Reconstruction. Video Processing and Computational Video 2010: 104-123 - [c87]Bastian Goldlücke, Daniel Cremers:
Convex Relaxation for Multilabel Problems with Product Label Spaces. ECCV (5) 2010: 225-238 - [c86]Jan Stühmer, Stefan Gumhold, Daniel Cremers:
Parallel Generalized Thresholding Scheme for Live Dense Geometry from a Handheld Camera. ECCV Workshops (1) 2010: 450-462 - [c85]Kalin Kolev, Thomas Pock, Daniel Cremers:
Anisotropic Minimal Surfaces Integrating Photoconsistency and Normal Information for Multiview Stereo. ECCV (3) 2010: 538-551 - [c84]Marek Schikora, Daniel Bender, Daniel Cremers, Wolfgang Koch:
Passive multi-object localization and tracking using bearing data. FUSION 2010: 1-7 - [c83]Marek Schikora, Adam Schikora, Karl-Heinz Kogel, Wolfgang Koch, Daniel Cremers:
Probabilistic Classification of Disease symptoms caused by Salmonella on Arabidopsis Plants. GI Jahrestagung (2) 2010: 874-879 - [c82]Markus Boerdgen, Benjamin Berkels, Martin Rumpf, Daniel Cremers:
Convex Relaxation for Grain Segmentation at Atomic Scale. VMV 2010: 179-186 - [e5]Daniel Cremers, Marcus A. Magnor, Lihi Zelnik-Manor:
Computational Video, 10.10. - 15.10.2010. Dagstuhl Seminar Proceedings 10411, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2010 [contents] - [i3]Daniel Cremers, Marcus A. Magnor, Lihi Zelnik-Manor:
10411 Abstracts Collection - Computational Video. Computational Video 2010 - [i2]Daniel Cremers, Marcus A. Magnor, Lihi Zelnik-Manor:
10411 Executive Summary - Computational Video. Computational Video 2010
2000 – 2009
- 2009
- [j17]Kalin Kolev, Maria Klodt, Thomas Brox, Daniel Cremers:
Continuous Global Optimization in Multiview 3D Reconstruction. Int. J. Comput. Vis. 84(1): 80-96 (2009) - [j16]Thomas Brox, Daniel Cremers:
On Local Region Models and a Statistical Interpretation of the Piecewise Smooth Mumford-Shah Functional. Int. J. Comput. Vis. 84(2): 184-193 (2009) - [j15]Andreas Wedel, Hernán Badino, Clemens Rabe, Heidi Loose, Uwe Franke, Daniel Cremers:
B-Spline Modeling of Road Surfaces With an Application to Free-Space Estimation. IEEE Trans. Intell. Transp. Syst. 10(4): 572-583 (2009) - [c81]Manuel Werlberger, Werner Trobin, Thomas Pock, Andreas Wedel, Daniel Cremers, Horst Bischof:
Anisotropic Huber-L1 Optical Flow. BMVC 2009: 1-11 - [c80]Frank R. Schmidt, Eno Töppe, Daniel Cremers:
Efficient planar graph cuts with applications in Computer Vision. CVPR 2009: 351-356 - [c79]Thomas Pock, Antonin Chambolle, Daniel Cremers, Horst Bischof:
A convex relaxation approach for computing minimal partitions. CVPR 2009: 810-817 - [c78]Kalin Kolev, Daniel Cremers:
Continuous ratio optimization via convex relaxation with applications to multiview 3D reconstruction. CVPR 2009: 1858-1864 - [c77]Frank R. Schmidt, Daniel Cremers:
A Closed-Form Solution for Image Sequence Segmentation with Dynamical Shape Priors. DAGM-Symposium 2009: 31-40 - [c76]Martin R. Oswald, Eno Töppe, Kalin Kolev, Daniel Cremers:
Non-parametric Single View Reconstruction of Curved Objects Using Convex Optimization. DAGM-Symposium 2009: 171-180 - [c75]Bastian Goldlücke, Daniel Cremers:
A Superresolution Framework for High-Accuracy Multiview Reconstruction. DAGM-Symposium 2009: 342-351 - [c74]Dennis Mitzel, Thomas Pock, Thomas Schoenemann, Daniel Cremers:
Video Super Resolution Using Duality Based TV-L1 Optical Flow. DAGM-Symposium 2009: 432-441 - [c73]Andreas Wedel, Annemarie Meißner, Clemens Rabe, Uwe Franke, Daniel Cremers:
Detection and Segmentation of Independently Moving Objects from Dense Scene Flow. EMMCVPR 2009: 14-27 - [c72]Thomas Schoenemann, Fredrik Kahl, Daniel Cremers:
Curvature regularity for region-based image segmentation and inpainting: A linear programming relaxation. ICCV 2009: 17-23 - [c71]Thomas Windheuser, Thomas Schoenemann, Daniel Cremers:
Beyond connecting the dots: A polynomial-time algorithm for segmentation and boundary estimation with imprecise user input. ICCV 2009: 717-722 - [c70]Thomas Pock, Daniel Cremers, Horst Bischof, Antonin Chambolle:
An algorithm for minimizing the Mumford-Shah functional. ICCV 2009: 1133-1140 - [c69]Frank Steinbrücker, Thomas Pock, Daniel Cremers:
Large displacement optical flow computation withoutwarping. ICCV 2009: 1609-1614 - [c68]Andreas Wedel, Daniel Cremers, Thomas Pock, Horst Bischof:
Structure- and motion-adaptive regularization for high accuracy optic flow. ICCV 2009: 1663-1668 - [c67]Bastian Goldlücke, Daniel Cremers:
Superresolution texture maps for multiview reconstruction. ICCV 2009: 1677-1684 - [c66]Anita Sellent, Martin Eisemann, Bastian Goldlücke, Thomas Pock, Daniel Cremers, Marcus A. Magnor:
Variational Optical Flow from Alternate Exposure Images. VMV 2009: 135-144 - [c65]Frank Steinbrücker, Thomas Pock, Daniel Cremers:
Advanced Data Terms for Variational Optic Flow Estimation. VMV 2009: 155-164 - [e4]Daniel Cremers, Bodo Rosenhahn, Alan L. Yuille, Frank R. Schmidt:
Statistical and Geometrical Approaches to Visual Motion Analysis, International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008. Revised Papers. Lecture Notes in Computer Science 5604, Springer 2009, ISBN 978-3-642-03060-4 [contents] - [e3]Daniel Cremers, Yuri Boykov, Andrew Blake, Frank R. Schmidt:
Energy Minimization Methods in Computer Vision and Pattern Recognition, 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009. Proceedings. Lecture Notes in Computer Science 5681, Springer 2009, ISBN 978-3-642-03640-8 [contents] - 2008
- [j14]Hailin Jin, Daniel Cremers, Dejun Wang, Emmanuel Prados, Anthony J. Yezzi, Stefano Soatto:
3-D Reconstruction of Shaded Objects from Multiple Images Under Unknown Illumination. Int. J. Comput. Vis. 76(3): 245-256 (2008) - [j13]Daniel Cremers:
Nonlinear Dynamical Shape Priors for Level Set Segmentation. J. Sci. Comput. 35(2-3): 132-143 (2008) - [j12]Thomas Brox, Oliver Kleinschmidt, Daniel Cremers:
Efficient Nonlocal Means for Denoising of Textural Patterns. IEEE Trans. Image Process. 17(7): 1083-1092 (2008) - [c64]Thomas Schoenemann, Frank R. Schmidt, Daniel Cremers:
Image Segmentation with Elastic Shape Priors via Global Geodesics in Product Spaces. BMVC 2008: 1-10 - [c63]Markus Unger, Thomas Pock, Werner Trobin, Daniel Cremers, Horst Bischof:
TVSeg - Interactive Total Variation Based Image Segmentation. BMVC 2008: 1-10 - [c62]Daniel Cremers, Frank R. Schmidt, Frank Barthel:
Shape priors in variational image segmentation: Convexity, Lipschitz continuity and globally optimal solutions. CVPR 2008 - [c61]Thomas Pock, Markus Unger, Daniel Cremers, Horst Bischof:
Fast and exact solution of Total Variation models on the GPU. CVPR Workshops 2008: 1-8 - [c60]Bodo Rosenhahn, Christian Schmaltz, Thomas Brox, Joachim Weickert, Daniel Cremers, Hans-Peter Seidel:
Markerless motion capture of man-machine interaction. CVPR 2008 - [c59]Thomas Schoenemann, Daniel Cremers:
High resolution motion layer decomposition using dual-space graph cuts. CVPR 2008 - [c58]Thomas Schoenemann, Daniel Cremers:
Globally optimal shape-based tracking in real-time. CVPR 2008 - [c57]Thomas Schoenemann, Daniel Cremers:
Matching non-rigidly deformable shapes across images: A globally optimal solution. CVPR 2008 - [c56]Werner Trobin, Thomas Pock, Daniel Cremers, Horst Bischof:
An Unbiased Second-Order Prior for High-Accuracy Motion Estimation. DAGM-Symposium 2008: 396-405 - [c55]Andreas Wedel, Thomas Pock, Christopher Zach, Horst Bischof, Daniel Cremers:
An Improved Algorithm for TV-L 1 Optical Flow. Statistical and Geometrical Approaches to Visual Motion Analysis 2008: 23-45 - [c54]Andreas Wedel, Tobi Vaudrey, Annemarie Meißner, Clemens Rabe, Thomas Brox, Uwe Franke, Daniel Cremers:
An Evaluation Approach for Scene Flow with Decoupled Motion and Position. Statistical and Geometrical Approaches to Visual Motion Analysis 2008: 46-69 - [c53]Maria Klodt, Thomas Schoenemann, Kalin Kolev, Marek Schikora, Daniel Cremers:
An Experimental Comparison of Discrete and Continuous Shape Optimization Methods. ECCV (1) 2008: 332-345 - [c52]Werner Trobin, Thomas Pock, Daniel Cremers, Horst Bischof:
Continuous Energy Minimization Via Repeated Binary Fusion. ECCV (4) 2008: 677-690 - [c51]Andreas Wedel, Clemens Rabe, Tobi Vaudrey, Thomas Brox, Uwe Franke, Daniel Cremers:
Efficient Dense Scene Flow from Sparse or Dense Stereo Data. ECCV (1) 2008: 739-751 - [c50]Kalin Kolev, Daniel Cremers:
Integration of Multiview Stereo and Silhouettes Via Convex Functionals on Convex Domains. ECCV (1) 2008: 752-765 - [c49]Thomas Pock, Thomas Schoenemann, Gottfried Graber, Horst Bischof, Daniel Cremers:
A Convex Formulation of Continuous Multi-label Problems. ECCV (3) 2008: 792-805 - [c48]Bodo Rosenhahn, Thomas Brox, Daniel Cremers, Hans-Peter Seidel:
Modeling and Tracking Line-Constrained Mechanical Systems. RobVis 2008: 98-110 - [e2]Daniel Cremers, Bodo Rosenhahn, Alan L. Yuille:
Statistical and Geometrical Approaches to Visual Motion Analysis, 13.07. - 18.07.2008. Dagstuhl Seminar Proceedings 08291, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2008 [contents] - [i1]Daniel Cremers, Bodo Rosenhahn, Alan L. Yuille:
08291 Abstracts Collection - Statistical and Geometrical Approaches to Visual Motion Analysis. Statistical and Geometrical Approaches to Visual Motion Analysis 2008 - 2007
- [j11]Daniel Cremers, Mikaël Rousson, Rachid Deriche:
A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape. Int. J. Comput. Vis. 72(2): 195-215 (2007) - [c47]Daniel Cremers:
Nonlinear Dynamical Shape Priors for Level Set Segmentation. CVPR 2007 - [c46]Bodo Rosenhahn, Thomas Brox, Daniel Cremers, Hans-Peter Seidel:
Online Smoothing for Markerless Motion Capture. DAGM-Symposium 2007: 163-172 - [c45]Christian Schmaltz, Bodo Rosenhahn, Thomas Brox, Joachim Weickert, Daniel Cremers, Lennart Wietzke, Gerald Sommer:
Occlusion Modeling by Tracking Multiple Objects. DAGM-Symposium 2007: 173-183 - [c44]Andreas Wedel, Thomas Schoenemann, Thomas Brox, Daniel Cremers:
WarpCut - Fast Obstacle Segmentation in Monocular Video. DAGM-Symposium 2007: 264-273 - [c43]Frank R. Schmidt, Eno Töppe, Daniel Cremers, Yuri Boykov:
Intrinsic Mean for Semi-metrical Shape Retrieval Via Graph Cuts. DAGM-Symposium 2007: 446-455 - [c42]Frank R. Schmidt, Eno Töppe, Daniel Cremers, Yuri Boykov:
Efficient Shape Matching Via Graph Cuts. EMMCVPR 2007: 39-54 - [c41]Kalin Kolev, Maria Klodt, Thomas Brox, Selim Esedoglu, Daniel Cremers:
Continuous Global Optimization in Multiview 3D Reconstruction. EMMCVPR 2007: 441-452 - [c40]Thomas Brox, Bodo Rosenhahn, Daniel Cremers, Hans-Peter Seidel:
Nonparametric Density Estimation with Adaptive, Anisotropic Kernels for Human Motion Tracking. Workshop on Human Motion 2007: 152-165 - [c39]Christian Schmaltz, Bodo Rosenhahn, Thomas Brox, Daniel Cremers, Joachim Weickert, Lennart Wietzke, Gerald Sommer:
Region-Based Pose Tracking. IbPRIA (2) 2007: 56-63 - [c38]Frank R. Schmidt, Dirk Farin, Daniel Cremers:
Fast Matching of Planar Shapes in Sub-cubic Runtime. ICCV 2007: 1-6 - [c37]Thomas Schoenemann, Daniel Cremers:
Globally Optimal Image Segmentation with an Elastic Shape Prior. ICCV 2007: 1-6 - [c36]Thomas Schoenemann, Daniel Cremers:
Introducing Curvature into Globally Optimal Image Segmentation: Minimum Ratio Cycles on Product Graphs. ICCV 2007: 1-6 - [c35]Daniel Cremers, Oliver Fluck, Mikaël Rousson, Shmuel Aharon:
A probabilistic level set formulation for interactive organ segmentation. Image Processing 2007: 65120V - [c34]Thomas Brox, Daniel Cremers:
Iterated Nonlocal Means for Texture Restoration. SSVM 2007: 13-24 - [c33]Thomas Brox, Daniel Cremers:
On the Statistical Interpretation of the Piecewise Smooth Mumford-Shah Functional. SSVM 2007: 203-213 - [e1]Alan L. Yuille, Song Chun Zhu, Daniel Cremers, Yongtian Wang:
Energy Minimization Methods in Computer Vision and Pattern Recognition, 6th International Conference, EMMCVPR 2007, Ezhou, China, August 27-29, 2007, Proceedings. Lecture Notes in Computer Science 4679, Springer 2007, ISBN 978-3-540-74195-4 [contents] - 2006
- [j10]Daniel Cremers, Nir A. Sochen, Christoph Schnörr:
A Multiphase Dynamic Labeling Model for Variational Recognition-driven Image Segmentation. Int. J. Comput. Vis. 66(1): 67-81 (2006) - [j9]Daniel Cremers, Stanley J. Osher, Stefano Soatto:
Kernel Density Estimation and Intrinsic Alignment for Shape Priors in Level Set Segmentation. Int. J. Comput. Vis. 69(3): 335-351 (2006) - [j8]Daniel Cremers:
Dynamical Statistical Shape Priors for Level Set-Based Tracking. IEEE Trans. Pattern Anal. Mach. Intell. 28(8): 1262-1273 (2006) - [j7]Siddharth Manay, Daniel Cremers, Byung-Woo Hong, Anthony J. Yezzi, Stefano Soatto:
Integral Invariants for Shape Matching. IEEE Trans. Pattern Anal. Mach. Intell. 28(10): 1602-1618 (2006) - [c32]Daniel Cremers, Christoph Guetter, Chenyang Xu:
Nonparametric Priors on the Space of Joint Intensity Distributions for Non-Rigid Multi-Modal Image Registration. CVPR (2) 2006: 1777-1783 - [c31]Frank R. Schmidt, Michael Clausen, Daniel Cremers:
Shape Matching by Variational Computation of Geodesics on a Manifold. DAGM-Symposium 2006: 142-151 - [c30]Thomas Schoenemann, Daniel Cremers:
Near Real-Time Motion Segmentation Using Graph Cuts. DAGM-Symposium 2006: 455-464 - [c29]Andreas Wedel, Uwe Franke, Jens Klappstein, Thomas Brox, Daniel Cremers:
Realtime Depth Estimation and Obstacle Detection from Monocular Video. DAGM-Symposium 2006: 475-484 - [c28]Thomas Brox, Bodo Rosenhahn, Uwe G. Kersting, Daniel Cremers:
Nonparametric Density Estimation for Human Pose Tracking. DAGM-Symposium 2006: 546-555 - [c27]Kalin Kolev, Thomas Brox, Daniel Cremers:
Robust Variational Segmentation of 3D Objects from Multiple Views. DAGM-Symposium 2006: 688-697 - [c26]Thomas Brox, Bodo Rosenhahn, Daniel Cremers:
Contours, Optic Flow, and Prior Knowledge: Cues for Capturing 3D Human Motion in Videos. Human Motion 2006: 265-293 - [c25]Thomas Brox, Bodo Rosenhahn, Daniel Cremers, Hans-Peter Seidel:
High Accuracy Optical Flow Serves 3-D Pose Tracking: Exploiting Contour and Flow Based Constraints. ECCV (2) 2006: 98-111 - [c24]Daniel Cremers, Leo J. Grady:
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts. ECCV (3) 2006: 263-274 - [c23]Yuri Boykov, Vladimir Kolmogorov, Daniel Cremers, Andrew Delong:
An Integral Solution to Surface Evolution PDEs Via Geo-cuts. ECCV (3) 2006: 409-422 - [c22]Bodo Rosenhahn, Thomas Brox, Daniel Cremers, Hans-Peter Seidel:
A Comparison of Shape Matching Methods for Contour Based Pose Estimation. IWCIA 2006: 263-276 - [c21]Timo Kohlberger, Daniel Cremers, Mikaël Rousson, Ramamani Ramaraj, Gareth Funka-Lea:
4D Shape Priors for a Level Set Segmentation of the Left Myocardium in SPECT Sequences. MICCAI (1) 2006: 92-100 - [c20]Oliver Fluck, Shmuel Aharon, Daniel Cremers, Mikaël Rousson:
GPU histogram computation. SIGGRAPH Research Posters 2006: 53 - [p3]Martin Bergtholdt, Daniel Cremers, Christoph Schnörr:
Variational Segmentation with Shape Priors. Handbook of Mathematical Models in Computer Vision 2006: 131-143 - [p2]Siddharth Manay, Daniel Cremers, Byung-Woo Hong, Anthony J. Yezzi, Stefano Soatto:
Integral Invariants and Shape Matching. Statistics and Analysis of Shapes 2006: 137-166 - 2005
- [c19]Siddharth Manay, Daniel Cremers, Anthony J. Yezzi, Stefano Soatto:
One-Shot Integral Invariant Shape Priors for Variational Segmentation. EMMCVPR 2005: 414-426 - [c18]Mikaël Rousson, Daniel Cremers:
Efficient Kernel Density Estimation of Shape and Intensity Priors for Level Set Segmentation. MICCAI (2) 2005: 757-764 - [c17]Daniel Cremers, Gareth Funka-Lea:
Dynamical Statistical Shape Priors for Level Set Based Sequence Segmentation. VLSM 2005: 210-221 - 2004
- [j6]Daniel Cremers, Stefano Soatto:
Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation. Int. J. Comput. Vis. 62(3): 249-265 (2004) - [c16]Hailin Jin, Daniel Cremers, Anthony J. Yezzi, Stefano Soatto:
Shedding Light on Stereoscopic Segmentation. CVPR (1) 2004: 36-42 - [c15]Daniel Cremers, Stanley J. Osher, Stefano Soatto:
Kernel Density Estimation and Intrinsic Alignment for Knowledge-Driven Segmentation: Teaching Level Sets to Walk. DAGM-Symposium 2004: 36-44 - [c14]Daniel Cremers, Nir A. Sochen, Christoph Schnörr:
Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. ECCV (4) 2004: 74-86 - [c13]Daniel Cremers:
Bayesian Approaches to Motion-Based Image and Video Segmentation. IWCM 2004: 104-123 - 2003
- [j5]Daniel Cremers, Christoph Schnörr:
Statistical shape knowledge in variational motion segmentation. Image Vis. Comput. 21(1): 77-86 (2003) - [j4]Jens Keuchel, Christoph Schnörr, Christian Schellewald, Daniel Cremers:
Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming. IEEE Trans. Pattern Anal. Mach. Intell. 25(11): 1364-1379 (2003) - [j3]Daniel Cremers, Timo Kohlberger, Christoph Schnörr:
Shape statistics in kernel space for variational image segmentation. Pattern Recognit. 36(9): 1929-1943 (2003) - [c12]Daniel Cremers:
A Variational Framework for Image Segmentation Combining Motion Estimation and Shape Regularization. CVPR (1) 2003: 53-58 - [c11]Daniel Cremers, Alan L. Yuille:
A Generative Model Based Approach to Motion Segmentation. DAGM-Symposium 2003: 313-320 - [c10]Daniel Cremers, Stefano Soatto:
Variational Space-Time Motion Segmentation. ICCV 2003: 886-893 - [c9]Gianfranco Doretto, Daniel Cremers, Paolo Favaro, Stefano Soatto:
Dynamic Texture Segmentation. ICCV 2003: 1236-1242 - [c8]Daniel Cremers, Nir A. Sochen, Christoph Schnörr:
Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling. Scale-Space 2003: 388-400 - [c7]Daniel Cremers:
A Multiphase Level Set Framework for Motion Segmentation. Scale-Space 2003: 599-614 - 2002
- [b1]Daniel Cremers:
Statistical shape knowledge in variational image segmentation. University of Mannheim, Germany, 2002, pp. I-X, 1-151 - [j2]Daniel Cremers, Florian Tischhäuser, Joachim Weickert, Christoph Schnörr:
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional. Int. J. Comput. Vis. 50(3): 295-313 (2002) - [j1]Daniel Cremers, Andreas V. M. Herz:
Traveling Waves of Excitation in Neural Field Models: Equivalence of Rate Descriptions and Integrate-and-Fire Dynamics. Neural Comput. 14(7): 1651-1667 (2002) - [c6]Jens Keuchel, Christoph Schnörr, Christian Schellewald, Daniel Cremers:
Unsupervised Image Partitioning with Semidefinite Programming. DAGM-Symposium 2002: 141-149 - [c5]Daniel Cremers, Christoph Schnörr:
Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization. DAGM-Symposium 2002: 472-480 - [c4]Daniel Cremers, Timo Kohlberger, Christoph Schnörr:
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation. ECCV (2) 2002: 93-108 - [p1]Daniel Cremers:
Statistisches Formenwissen in Variationsansätzen zur Bildsegmentierung. Ausgezeichnete Informatikdissertationen 2002: 19-28 - 2001
- [c3]Daniel Cremers, Timo Kohlberger, Christoph Schnörr:
Nonlinear Shape Statistics via Kernel Spaces. DAGM-Symposium 2001: 269-276 - [c2]Jens Keuchel, Christian Schellewald, Daniel Cremers, Christoph Schnörr:
Convex Relaxations for Binary Image Partitioning and Perceptual Grouping. DAGM-Symposium 2001: 353-360 - 2000
- [c1]Daniel Cremers, Christoph Schnörr, Joachim Weickert, Christian Schellewald:
Diffusion-Snakes Using Statistical Shape Knowledge. AFPAC 2000: 164-174
Coauthor Index
aka: Bastian Goldluecke
aka: Qadeer Khan
aka: Martin Ralf Oswald
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