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Janis Keuper
Janis Fehr
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- affiliation: Saarland University, Saarbrücken, Germany
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2020 – today
- 2024
- [j4]Julia Grabinski, Janis Keuper, Margret Keuper:
As large as it gets - Studying Infinitely Large Convolutions via Neural Implicit Frequency Filters. Trans. Mach. Learn. Res. 2024 (2024) - [c48]Paul Gavrikov, Janis Keuper:
Can Biases in ImageNet Models Explain Generalization? CVPR 2024: 22184-22194 - [c47]Peter Lorenz, Ricard Durall, Janis Keuper:
Adversarial Examples are Misaligned in Diffusion Model Manifolds. IJCNN 2024: 1-8 - [c46]Lars Nieradzik, Henrike Stephani, Jördis Sieburg-Rockel, Stephanie Helmling, Andrea Olbrich, Janis Keuper:
Challenging the Black Box: A Comprehensive Evaluation of Attribution Maps of CNN Applications in Agriculture and Forestry. VISIGRAPP (2): VISAPP 2024: 483-492 - [i60]Peter Lorenz, Ricard Durall, Janis Keuper:
Adversarial Examples are Misaligned in Diffusion Model Manifolds. CoRR abs/2401.06637 (2024) - [i59]Lars Nieradzik, Henrike Stephani, Jördis Sieburg-Rockel, Stephanie Helmling, Andrea Olbrich, Janis Keuper:
Challenging the Black Box: A Comprehensive Evaluation of Attribution Maps of CNN Applications in Agriculture and Forestry. CoRR abs/2402.11670 (2024) - [i58]Paul Gavrikov, Jovita Lukasik, Steffen Jung, Robert Geirhos, Bianca Lamm, Muhammad Jehanzeb Mirza, Margret Keuper, Janis Keuper:
Are Vision Language Models Texture or Shape Biased and Can We Steer Them? CoRR abs/2403.09193 (2024) - [i57]Martin Spitznagel, Janis Keuper:
Urban Sound Propagation: a Benchmark for 1-Step Generative Modeling of Complex Physical Systems. CoRR abs/2403.10904 (2024) - [i56]Patrick Grommelt, Louis Weiss, Franz-Josef Pfreundt, Janis Keuper:
Fake or JPEG? Revealing Common Biases in Generated Image Detection Datasets. CoRR abs/2403.17608 (2024) - [i55]Paul Gavrikov, Janis Keuper:
Can Biases in ImageNet Models Explain Generalization? CoRR abs/2404.01509 (2024) - [i54]Luisa Schwirten, Jannes Scholz, Daniel Kondermann, Janis Keuper:
Ambiguous Annotations: When is a Pedestrian not a Pedestrian? CoRR abs/2405.08794 (2024) - [i53]Shashank Agnihotri, Julia Grabinski, Janis Keuper, Margret Keuper:
Beware of Aliases - Signal Preservation is Crucial for Robust Image Restoration. CoRR abs/2406.07435 (2024) - [i52]Bianca Lamm, Janis Keuper:
Can Visual Language Models Replace OCR-Based Visual Question Answering Pipelines in Production? A Case Study in Retail. CoRR abs/2408.15626 (2024) - [i51]Lars Nieradzik, Henrike Stephani, Janis Keuper:
Top-GAP: Integrating Size Priors in CNNs for more Interpretability, Robustness, and Bias Mitigation. CoRR abs/2409.04819 (2024) - [i50]Paul Gavrikov, Shashank Agnihotri, Margret Keuper, Janis Keuper:
How Do Training Methods Influence the Utilization of Vision Models? CoRR abs/2410.14470 (2024) - 2023
- [j3]Ricard Durall
, Ammar Ghanim, Mario Ruben Fernandez, Norman Ettrich, Janis Keuper:
Deep diffusion models for seismic processing. Comput. Geosci. 177: 105377 (2023) - [j2]Jovita Lukasik, Paul Gavrikov, Janis Keuper, Margret Keuper:
Improving Native CNN Robustness with Filter Frequency Regularization. Trans. Mach. Learn. Res. 2023 (2023) - [c45]Paul Gavrikov
An Extended Study of Human-like Behavior under Adversarial Training. CVPR Workshops 2023: 2361-2368 - [c44]Peter Lorenz, Ricard L. Durall, Janis Keuper:
Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality. ICCV (Workshops) 2023: 448-459 - [c43]Paul Gavrikov
On the Interplay of Convolutional Padding and Adversarial Robustness. ICCV (Workshops) 2023: 3983-3992 - [c42]Peter Lorenz, Margret Keuper, Janis Keuper:
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection. VISIGRAPP (5: VISAPP) 2023: 27-38 - [i49]Paul Gavrikov, Janis Keuper:
Rethinking 1x1 Convolutions: Can we train CNNs with Frozen Random Filters? CoRR abs/2301.11360 (2023) - [i48]Paul Gavrikov
An Extended Study of Human-like Behavior under Adversarial Training. CoRR abs/2303.12669 (2023) - [i47]Daniel Ladwig, Bianca Lamm, Janis Keuper:
Fine-Grained Product Classification on Leaflet Advertisements. CoRR abs/2305.03706 (2023) - [i46]Janis Keuper:
On Invariance, Equivariance, Correlation and Convolution of Spherical Harmonic Representations for Scalar and Vectorial Data. CoRR abs/2307.03311 (2023) - [i45]Lars Nieradzik, Jördis Sieburg-Rockel, Stephanie Helmling, Janis Keuper, Thomas Weibel, Andrea Olbrich, Henrike Stephani:
Automating Wood Species Detection and Classification in Microscopic Images of Fibrous Materials with Deep Learning. CoRR abs/2307.09588 (2023) - [i44]Julia Grabinski, Janis Keuper, Margret Keuper:
Fix your downsampling ASAP! Be natively more robust via Aliasing and Spectral Artifact free Pooling. CoRR abs/2307.09804 (2023) - [i43]Julia Grabinski, Janis Keuper, Margret Keuper:
As large as it gets: Learning infinitely large Filters via Neural Implicit Functions in the Fourier Domain. CoRR abs/2307.10001 (2023) - [i42]Paul Gavrikov
On the Interplay of Convolutional Padding and Adversarial Robustness. CoRR abs/2308.06612 (2023) - [i41]Paul Gavrikov
Don't Look into the Sun: Adversarial Solarization Attacks on Image Classifiers. CoRR abs/2308.12661 (2023) - [i40]Bianca Lamm, Janis Keuper:
Retail-786k: a Large-Scale Dataset for Visual Entity Matching. CoRR abs/2309.17164 (2023) - 2022
- [j1]Julia Grabinski
Aliasing and adversarial robust generalization of CNNs. Mach. Learn. 111(11): 3925-3951 (2022) - [c41]Paul Gavrikov
Adversarial Robustness through the Lens of Convolutional Filters. CVPR Workshops 2022: 138-146 - [c40]Paul Gavrikov
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters. CVPR 2022: 19044-19054 - [c39]Julia Grabinski
FrequencyLowCut Pooling - Plug and Play Against Catastrophic Overfitting. ECCV (14) 2022: 36-57 - [c38]Julia Grabinski, Paul Gavrikov, Janis Keuper, Margret Keuper:
Robust Models are less Over-Confident. NeurIPS 2022 - [i39]Paul Gavrikov, Janis Keuper:
An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters. CoRR abs/2201.08465 (2022) - [i38]Paul Gavrikov
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters. CoRR abs/2203.15331 (2022) - [i37]Julia Grabinski, Steffen Jung, Janis Keuper, Margret Keuper:
FrequencyLowCut Pooling - Plug & Play against Catastrophic Overfitting. CoRR abs/2204.00491 (2022) - [i36]Paul Gavrikov
Adversarial Robustness through the Lens of Convolutional Filters. CoRR abs/2204.02481 (2022) - [i35]Ricard Durall, Ammar Ghanim, Norman Ettrich, Janis Keuper:
Dissecting U-net for Seismic Application: An In-Depth Study on Deep Learning Multiple Removal. CoRR abs/2206.12112 (2022) - [i34]Paula Harder, Duncan Watson-Parris
Physics-Informed Learning of Aerosol Microphysics. CoRR abs/2207.11786 (2022) - [i33]Julia Grabinski, Paul Gavrikov
Robust Models are less Over-Confident. CoRR abs/2210.05938 (2022) - [i32]Paul Gavrikov
Does Medical Imaging learn different Convolution Filters? CoRR abs/2210.13799 (2022) - [i31]Peter Lorenz, Margret Keuper, Janis Keuper:
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection. CoRR abs/2212.06776 (2022) - 2021
- [c37]Ricard Durall Lopez, Jireh Jam, Dominik Strassel, Moi Hoon Yap, Janis Keuper:
FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces. BMVC 2021: 246 - [c36]Sebastian Hoch, Sascha Lange, Janis Keuper:
Sample efficient localization and stage prediction with autoencoders. ESANN 2021 - [c35]Paula Harder, Franz-Josef Pfreundt, Margret Keuper, Janis Keuper:
SpectralDefense: Detecting Adversarial Attacks on CNNs in the Fourier Domain. IJCNN 2021: 1-8 - [c34]Ricard Durall, Stanislav Frolov, Jörn Hees, Federico Raue, Franz-Josef Pfreundt, Andreas Dengel, Janis Keuper:
Combining Transformer Generators with Convolutional Discriminators. KI 2021: 67-79 - [c33]Kalun Ho, Avraam Chatzimichailidis, Margret Keuper, Janis Keuper:
MSM: Multi-stage Multicuts for Scalable Image Clustering. ISC Workshops 2021: 267-284 - [c32]Ricard Durall, Franz-Josef Pfreundt, Janis Keuper:
Stabilizing GANs with Soft Octave Convolutions. VISIGRAPP (4: VISAPP) 2021: 15-23 - [c31]Ricard Durall, Kalun Ho, Franz-Josef Pfreundt, Janis Keuper:
Latent Space Conditioning on Generative Adversarial Networks. VISIGRAPP (4: VISAPP) 2021: 24-34 - [c30]Ricard Durall, Avraam Chatzimichailidis, Peter Labus, Janis Keuper:
Combating Mode Collapse in GAN Training: An Empirical Analysis using Hessian Eigenvalues. VISIGRAPP (4: VISAPP) 2021: 211-218 - [i30]Paula Harder, Franz-Josef Pfreundt, Margret Keuper, Janis Keuper:
SpectralDefense: Detecting Adversarial Attacks on CNNs in the Fourier Domain. CoRR abs/2103.03000 (2021) - [i29]Febin Sebastian Elayanithottathil, Janis Keuper:
A Retail Product Categorisation Dataset. CoRR abs/2103.13864 (2021) - [i28]Ricard Durall, Stanislav Frolov, Andreas Dengel, Janis Keuper:
Combining Transformer Generators with Convolutional Discriminators. CoRR abs/2105.10189 (2021) - [i27]Kalun Ho, Franz-Josef Pfreundt, Janis Keuper, Margret Keuper:
Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space. CoRR abs/2106.12303 (2021) - [i26]Paula Harder, Duncan Watson-Parris
Emulating Aerosol Microphysics with Machine Learning. CoRR abs/2109.10593 (2021) - [i25]Ricard Durall, Jireh Jam, Dominik Strassel, Moi Hoon Yap, Janis Keuper:
FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces. CoRR abs/2110.09425 (2021) - [i24]Peter Lorenz, Paula Harder, Dominik Strassel, Margret Keuper, Janis Keuper:
Detecting AutoAttack Perturbations in the Frequency Domain. CoRR abs/2111.08785 (2021) - [i23]Peter Lorenz, Dominik Strassel, Margret Keuper, Janis Keuper:
Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness? CoRR abs/2112.01601 (2021) - [i22]Ricard Durall, Janis Keuper:
Investigating Shifts in GAN Output-Distributions. CoRR abs/2112.14061 (2021) - 2020
- [c29]Kalun Ho, Amirhossein Kardoost, Franz-Josef Pfreundt, Janis Keuper, Margret Keuper:
A Two-Stage Minimum Cost Multicut Approach to Self-supervised Multiple Person Tracking. ACCV (2) 2020: 539-557 - [c28]Ricard Durall, Margret Keuper, Janis Keuper:
Watch Your Up-Convolution: CNN Based Generative Deep Neural Networks Are Failing to Reproduce Spectral Distributions. CVPR 2020: 7887-7896 - [c27]Kalun Ho, Janis Keuper, Franz-Josef Pfreundt, Margret Keuper:
Learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches. ICPR 2020: 87-94 - [c26]Ricard Durall, Franz-Josef Pfreundt, Janis Keuper:
Local Facial Attribute Transfer through Inpainting. ICPR 2020: 95-102 - [c25]Dominik Straßel, Philipp Reusch, Janis Keuper:
Python Workflows on HPC Systems. PyHPC@SC 2020: 32-40 - [c24]Philipp Rombach, Janis Keuper:
SmartPred: Unsupervised Hard Disk Failure Detection. ISC Workshops 2020: 235-246 - [i21]Raju Ram, Sabine Müller, Franz-Josef Pfreundt, Nicolas R. Gauger, Janis Keuper:
Scalable Hyperparameter Optimization with Lazy Gaussian Processes. CoRR abs/2001.05726 (2020) - [i20]Kalun Ho, Janis Keuper, Margret Keuper:
Unsupervised Multiple Person Tracking using AutoEncoder-Based Lifted Multicuts. CoRR abs/2002.01192 (2020) - [i19]Ricard Durall, Franz-Josef Pfreundt, Janis Keuper:
Local Facial Attribute Transfer through Inpainting. CoRR abs/2002.03040 (2020) - [i18]Peter Michael Habelitz, Janis Keuper:
PHS: A Toolbox for Parallel Hyperparameter Search. CoRR abs/2002.11429 (2020) - [i17]Ricard Durall, Margret Keuper, Janis Keuper:
Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions. CoRR abs/2003.01826 (2020) - [i16]Kalun Ho, Janis Keuper, Franz-Josef Pfreundt, Margret Keuper:
Learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches. CoRR abs/2007.03123 (2020) - [i15]Dominik Strassel
Python Workflows on HPC Systems. CoRR abs/2012.00365 (2020) - [i14]Ricard Durall, Kalun Ho, Franz-Josef Pfreundt, Janis Keuper:
Latent Space Conditioning on Generative Adversarial Networks. CoRR abs/2012.08803 (2020) - [i13]Ricard Durall, Avraam Chatzimichailidis, Peter Labus, Janis Keuper:
Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues. CoRR abs/2012.09673 (2020)
2010 – 2019
- 2019
- [c23]Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe, Janis Keuper:
Object Segmentation Using Pixel-Wise Adversarial Loss. GCPR 2019: 303-316 - [c22]Ricard Durall, Franz-Josef Pfreundt, Janis Keuper:
Semi Few-Shot Attribute Translation. IVCNZ 2019: 1-8 - [c21]Raju Ram, Sabine Müller, Franz-Josef Pfreundt, Nicolas R. Gauger
Scalable Hyperparameter Optimization with Lazy Gaussian Processes. MLHPC@SC 2019: 56-65 - [c20]Avraam Chatzimichailidis, Janis Keuper, Franz-Josef Pfreundt, Nicolas R. Gauger
GradVis: Visualization and Second Order Analysis of Optimization Surfaces during the Training of Deep Neural Networks. MLHPC@SC 2019: 66-74 - [i12]Ricard Durall, Franz-Josef Pfreundt, Janis Keuper:
Stabilizing GANs with Octave Convolutions. CoRR abs/1905.12534 (2019) - [i11]Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe, Janis Keuper:
Object Segmentation using Pixel-wise Adversarial Loss. CoRR abs/1909.10341 (2019) - [i10]Avraam Chatzimichailidis, Franz-Josef Pfreundt, Nicolas R. Gauger, Janis Keuper:
GradVis: Visualization and Second Order Analysis of Optimization Surfaces during the Training of Deep Neural Networks. CoRR abs/1909.12108 (2019) - [i9]Ricard Durall, Franz-Josef Pfreundt, Janis Keuper:
Semi Few-Shot Attribute Translation. CoRR abs/1910.03240 (2019) - [i8]Ricard Durall, Margret Keuper, Franz-Josef Pfreundt, Janis Keuper:
Unmasking DeepFakes with simple Features. CoRR abs/1911.00686 (2019) - 2018
- [c19]Dominik Marek Loroch, Franz-Josef Pfreundt, Norbert Wehn
Sparsity in Deep Neural Networks - An Empirical Investigation with TensorQuant. DMLE/IOTSTREAMING@PKDD/ECML 2018: 5-20 - [i7]Dominik Marek Loroch, Franz-Josef Pfreundt, Norbert Wehn, Janis Keuper:
Sparsity in Deep Neural Networks - An Empirical Investigation with TensorQuant. CoRR abs/1808.08784 (2018) - 2017
- [c18]Dominik Marek Loroch, Franz-Josef Pfreundt, Norbert Wehn
TensorQuant: A Simulation Toolbox for Deep Neural Network Quantization. MLHPC@SC 2017: 1:1-1:8 - [i6]Martin Kuehn, Janis Keuper, Franz-Josef Pfreundt:
Using GPI-2 for Distributed Memory Paralleliziation of the Caffe Toolbox to Speed up Deep Neural Network Training. CoRR abs/1706.00095 (2017) - [i5]Valentin Tschannen
Facies classification from well logs using an inception convolutional network. CoRR abs/1706.00613 (2017) - [i4]Dominik Marek Loroch, Norbert Wehn, Franz-Josef Pfreundt, Janis Keuper:
TensorQuant - A Simulation Toolbox for Deep Neural Network Quantization. CoRR abs/1710.05758 (2017) - 2016
- [c17]Janis Keuper, Franz-Josef Pfreundt:
Distributed Training of Deep Neural Networks: Theoretical and Practical Limits of Parallel Scalability. MLHPC@SC 2016: 19-26 - [i3]Janis Keuper:
Distributed Training of Deep Neuronal Networks: Theoretical and Practical Limits of Parallel Scalability. CoRR abs/1609.06870 (2016) - 2015
- [c16]Janis Keuper, Franz-Josef Pfreundt:
Asynchronous parallel stochastic gradient descent: a numeric core for scalable distributed machine learning algorithms. MLHPC@SC 2015: 1:1-1:11 - [i2]Janis Keuper
Asynchronous Parallel Stochastic Gradient Descent - A Numeric Core for Scalable Distributed Machine Learning Algorithms. CoRR abs/1505.04956 (2015) - [i1]Janis Keuper, Franz-Josef Pfreundt:
Balancing the Communication Load of Asynchronously Parallelized Machine Learning Algorithms. CoRR abs/1510.01155 (2015) - 2011
- [c15]Sven Wanner, Janis Fehr
Generating EPI Representations of 4D Light Fields with a Single Lens Focused Plenoptic Camera. ISVC (1) 2011: 90-101 - [c14]Jens-Malte Gottfried, Janis Fehr
Computing Range Flow from Multi-modal Kinect Data. ISVC (1) 2011: 758-767 - 2010
- [c13]Janis Fehr
Local Rotation Invariant Patch Descriptors for 3D Vector Fields. ICPR 2010: 1381-1384
2000 – 2009
- 2009
- [b1]Janis Fehr:
Local invariant features for 3D image analysis. University of Freiburg, 2009 - [c12]Janis Fehr
A Bag of Features Approach for 3D Shape Retrieval. ISVC (1) 2009: 34-43 - [c11]Janis Fehr
Cross-Correlation and Rotation Estimation of Local 3D Vector Field Patches. ISVC (1) 2009: 287-296 - 2008
- [c10]Kersten Petersen, Janis Fehr
Fast Generalized Belief Propagation for MAP Estimation on 2D and 3D Grid-Like Markov Random Fields. DAGM-Symposium 2008: 41-50 - [c9]Janis Fehr, Marco Reisert, Hans Burkhardt:
Fast and Accurate Rotation Estimation on the 2-Sphere without Correspondences. ECCV (2) 2008: 239-251 - [c8]Janis Fehr, Hans Burkhardt:
3D rotation invariant local binary patterns. ICPR 2008: 1-4 - 2007
- [c7]Janis Fehr, Karina Zapien Arreola, Hans Burkhardt:
Fast Support Vector Machine Classification of Very Large Datasets. GfKl 2007: 11-18 - [c6]Janis Fehr, Hans Burkhardt:
Harmonic Shape Histograms for 3D Shape Classification and Retrieval. MVA 2007: 384-387 - 2006
- [c5]Janis Fehr, Catharina Sauer, Haymo Kurz, Olaf Ronneberger, Hans Burkhardt:
Identifikation von Zellen in intaktem Gewebe. Bildverarbeitung für die Medizin 2006: 369-373 - [c4]Janis Fehr, Hans Burkhardt:
Phase Based 3D Texture Features. DAGM-Symposium 2006: 263-272 - [c3]Karina Zapien Arreola, Janis Fehr
Fast Support Vector Machine Classification using linear SVMs. ICPR (3) 2006: 366-369 - 2005
- [c2]Olaf Ronneberger, Janis Fehr, Hans Burkhardt:
Voxel-Wise Gray Scale Invariants for Simultaneous Segmentation and Classification. DAGM-Symposium 2005: 85-92 - [c1]Janis Fehr, Olaf Ronneberger, Haymo Kurz, Hans Burkhardt:
Self-learning Segmentation and Classification of Cell-Nuclei in 3D Volumetric Data Using Voxel-Wise Gray Scale Invariants. DAGM-Symposium 2005: 377-384
Coauthor Index
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