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Philipp Krähenbühl
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- affiliation: University of Texas at Austin, Department of Computer Science, TX, USA
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2020 – today
- 2024
- [c46]Yue Zhao, Long Zhao, Xingyi Zhou, Jialin Wu, Chun-Te Chu, Hui Miao, Florian Schroff, Hartwig Adam, Ting Liu, Boqing Gong, Philipp Krähenbühl, Liangzhe Yuan:
Distilling Vision-Language Models on Millions of Videos. CVPR 2024: 13106-13116 - [c45]Jang Hyun Cho, Philipp Krähenbühl:
Language-Conditioned Detection Transformer. CVPR 2024: 16593-16603 - [i47]Yue Zhao, Long Zhao, Xingyi Zhou, Jialin Wu, Chun-Te Chu, Hui Miao, Florian Schroff, Hartwig Adam, Ting Liu, Boqing Gong, Philipp Krähenbühl, Liangzhe Yuan:
Distilling Vision-Language Models on Millions of Videos. CoRR abs/2401.06129 (2024) - [i46]Jang Hyun Cho, Boris Ivanovic, Yulong Cao, Edward Schmerling, Yue Wang, Xinshuo Weng, Boyi Li, Yurong You, Philipp Krähenbühl, Yan Wang, Marco Pavone:
Language-Image Models with 3D Understanding. CoRR abs/2405.03685 (2024) - [i45]Yue Zhao, Yuanjun Xiong, Philipp Krähenbühl:
Image and Video Tokenization with Binary Spherical Quantization. CoRR abs/2406.07548 (2024) - [i44]Shuhan Tan, Boris Ivanovic, Yuxiao Chen, Boyi Li, Xinshuo Weng, Yulong Cao, Philipp Krähenbühl, Marco Pavone:
Promptable Closed-loop Traffic Simulation. CoRR abs/2409.05863 (2024) - [i43]Santhosh Kumar Ramakrishnan, Erik Wijmans, Philipp Krähenbühl, Vladlen Koltun:
Does Spatial Cognition Emerge in Frontier Models? CoRR abs/2410.06468 (2024) - 2023
- [c44]Shuhan Tan, Boris Ivanovic, Xinshuo Weng, Marco Pavone, Philipp Krähenbühl:
Language Conditioned Traffic Generation. CoRL 2023: 2714-2752 - [c43]Yue Zhao, Ishan Misra, Philipp Krähenbühl, Rohit Girdhar:
Learning Video Representations from Large Language Models. CVPR 2023: 6586-6597 - [c42]Jang Hyun Cho, Philipp Krähenbühl, Vignesh Ramanathan:
PartDistillation: Learning Parts from Instance Segmentation. CVPR 2023: 7152-7161 - [c41]Jeffrey Ouyang-Zhang, Daniel Jesus Diaz, Adam R. Klivans, Philipp Krähenbühl:
Predicting a Protein's Stability under a Million Mutations. NeurIPS 2023 - [i42]Jang Hyun Cho, Philipp Krähenbühl:
Long-tail Detection with Effective Class-Margins. CoRR abs/2301.09724 (2023) - [i41]Shuhan Tan, Boris Ivanovic, Xinshuo Weng, Marco Pavone, Philipp Krähenbühl:
Language Conditioned Traffic Generation. CoRR abs/2307.07947 (2023) - [i40]Yue Zhao, Philipp Krähenbühl:
Training a Large Video Model on a Single Machine in a Day. CoRR abs/2309.16669 (2023) - [i39]Jang Hyun Cho, Philipp Krähenbühl:
Language-conditioned Detection Transformer. CoRR abs/2311.17902 (2023) - 2022
- [c40]Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl:
Simple Multi-dataset Detection. CVPR 2022: 7561-7570 - [c39]Xingyi Zhou, Tianwei Yin, Vladlen Koltun, Philipp Krähenbühl:
Global Tracking Transformers. CVPR 2022: 8761-8770 - [c38]Brady Zhou, Philipp Krähenbühl:
Cross-view Transformers for real-time Map-view Semantic Segmentation. CVPR 2022: 13750-13759 - [c37]Dian Chen, Philipp Krähenbühl:
Learning from All Vehicles. CVPR 2022: 17201-17210 - [c36]Xingyi Zhou, Rohit Girdhar, Armand Joulin, Philipp Krähenbühl, Ishan Misra:
Detecting Twenty-Thousand Classes Using Image-Level Supervision. ECCV (9) 2022: 350-368 - [c35]Yue Zhao
, Philipp Krähenbühl
Real-Time Online Video Detection with Temporal Smoothing Transformers. ECCV (34) 2022: 485-502 - [c34]Jang Hyun Cho
Long-tail Detection with Effective Class-Margins. ECCV (8) 2022: 698-714 - [i38]Xingyi Zhou, Rohit Girdhar, Armand Joulin, Philipp Krähenbühl, Ishan Misra:
Detecting Twenty-thousand Classes using Image-level Supervision. CoRR abs/2201.02605 (2022) - [i37]Dian Chen, Philipp Krähenbühl:
Learning from All Vehicles. CoRR abs/2203.11934 (2022) - [i36]Xingyi Zhou, Tianwei Yin, Vladlen Koltun, Philipp Krähenbühl:
Global Tracking Transformers. CoRR abs/2203.13250 (2022) - [i35]Brady Zhou, Philipp Krähenbühl:
Cross-view Transformers for real-time Map-view Semantic Segmentation. CoRR abs/2205.02833 (2022) - [i34]Yue Zhao, Philipp Krähenbühl:
Real-time Online Video Detection with Temporal Smoothing Transformers. CoRR abs/2209.09236 (2022) - [i33]Yue Zhao, Ishan Misra, Philipp Krähenbühl, Rohit Girdhar:
Learning Video Representations from Large Language Models. CoRR abs/2212.04501 (2022) - [i32]Jeffrey Ouyang-Zhang, Jang Hyun Cho, Xingyi Zhou, Philipp Krähenbühl:
NMS Strikes Back. CoRR abs/2212.06137 (2022) - 2021
- [c33]Chao-Yuan Wu, Philipp Krähenbühl:
Towards Long-Form Video Understanding. CVPR 2021: 1884-1894 - [c32]Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl:
Center-Based 3D Object Detection and Tracking. CVPR 2021: 11784-11793 - [c31]Dian Chen, Vladlen Koltun, Philipp Krähenbühl:
Learning to drive from a world on rails. ICCV 2021: 15570-15579 - [c30]Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram
Memory Optimization for Deep Networks. ICLR 2021 - [c29]Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl:
Multimodal Virtual Point 3D Detection. NeurIPS 2021: 16494-16507 - [i31]Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl:
Simple multi-dataset detection. CoRR abs/2102.13086 (2021) - [i30]Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl:
Probabilistic two-stage detection. CoRR abs/2103.07461 (2021) - [i29]Dian Chen
Learning to drive from a world on rails. CoRR abs/2105.00636 (2021) - [i28]Chao-Yuan Wu, Philipp Krähenbühl:
Towards Long-Form Video Understanding. CoRR abs/2106.11310 (2021) - [i27]Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl:
Multimodal Virtual Point 3D Detection. CoRR abs/2111.06881 (2021) - 2020
- [c28]Chao-Yuan Wu, Ross B. Girshick, Kaiming He, Christoph Feichtenhofer, Philipp Krähenbühl:
A Multigrid Method for Efficiently Training Video Models. CVPR 2020: 150-159 - [c27]Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl:
Tracking Objects as Points. ECCV (4) 2020: 474-490 - [c26]Brady Zhou
Domain Adaptation Through Task Distillation. ECCV (26) 2020: 664-680 - [i26]Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl:
Tracking Objects as Points. CoRR abs/2004.01177 (2020) - [i25]Sheng Cao, Chao-Yuan Wu, Philipp Krähenbühl:
Lossless Image Compression through Super-Resolution. CoRR abs/2004.02872 (2020) - [i24]Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl:
Center-based 3D Object Detection and Tracking. CoRR abs/2006.11275 (2020) - [i23]Brady Zhou, Nimit Kalra, Philipp Krähenbühl:
Domain Adaptation Through Task Distillation. CoRR abs/2008.11911 (2020) - [i22]Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl:
Memory Optimization for Deep Networks. CoRR abs/2010.14501 (2020)
2010 – 2019
- 2019
- [j4]Brady Zhou
Does computer vision matter for action? Sci. Robotics 4(30) (2019) - [c25]Dian Chen, Brady Zhou, Vladlen Koltun, Philipp Krähenbühl:
Learning by Cheating. CoRL 2019: 66-75 - [c24]Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krähenbühl, Ross B. Girshick:
Long-Term Feature Banks for Detailed Video Understanding. CVPR 2019: 284-293 - [c23]Xingyi Zhou, Jiacheng Zhuo, Philipp Krähenbühl:
Bottom-Up Object Detection by Grouping Extreme and Center Points. CVPR 2019: 850-859 - [c22]Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang, Ji Lin, Min Sun, Philipp Krähenbühl, Trevor Darrell, Fisher Yu:
Joint Monocular 3D Vehicle Detection and Tracking. ICCV 2019: 5389-5398 - [c21]Brady Zhou, Philipp Krähenbühl:
Don't let your Discriminator be fooled. ICLR (Poster) 2019 - [c20]Dequan Wang, Coline Devin, Qi-Zhi Cai, Philipp Krähenbühl, Trevor Darrell:
Monocular Plan View Networks for Autonomous Driving. IROS 2019: 2876-2883 - [i21]Xingyi Zhou, Jiacheng Zhuo, Philipp Krähenbühl:
Bottom-up Object Detection by Grouping Extreme and Center Points. CoRR abs/1901.08043 (2019) - [i20]Xingyi Zhou, Dequan Wang, Philipp Krähenbühl:
Objects as Points. CoRR abs/1904.07850 (2019) - [i19]Dequan Wang, Coline Devin, Qi-Zhi Cai, Philipp Krähenbühl, Trevor Darrell:
Monocular Plan View Networks for Autonomous Driving. CoRR abs/1905.06937 (2019) - [i18]Brady Zhou, Philipp Krähenbühl, Vladlen Koltun:
Does computer vision matter for action? CoRR abs/1905.12887 (2019) - [i17]Chao-Yuan Wu, Ross B. Girshick, Kaiming He, Christoph Feichtenhofer, Philipp Krähenbühl:
A Multigrid Method for Efficiently Training Video Models. CoRR abs/1912.00998 (2019) - [i16]Dian Chen
Learning by Cheating. CoRR abs/1912.12294 (2019) - 2018
- [c19]Philipp Krähenbühl:
Free Supervision From Video Games. CVPR 2018: 2955-2964 - [c18]Chao-Yuan Wu, Manzil Zaheer, Hexiang Hu
Compressed Video Action Recognition. CVPR 2018: 6026-6035 - [c17]Chao-Yuan Wu
Video Compression Through Image Interpolation. ECCV (8) 2018: 425-440 - [c16]Haoshuo Huang
Domain Transfer Through Deep Activation Matching. ECCV (16) 2018: 611-626 - [i15]Chao-Yuan Wu, Nayan Singhal, Philipp Krähenbühl:
Video Compression through Image Interpolation. CoRR abs/1804.06919 (2018) - [i14]Charles Packer, Katelyn Gao, Jernej Kos, Philipp Krähenbühl, Vladlen Koltun, Dawn Song:
Assessing Generalization in Deep Reinforcement Learning. CoRR abs/1810.12282 (2018) - [i13]Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang, Ji Lin, Min Sun, Philipp Krähenbühl, Trevor Darrell, Fisher Yu:
Joint Monocular 3D Vehicle Detection and Tracking. CoRR abs/1811.10742 (2018) - [i12]Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krähenbühl, Ross B. Girshick:
Long-Term Feature Banks for Detailed Video Understanding. CoRR abs/1812.05038 (2018) - 2017
- [j3]Shiry Ginosar, Kate Rakelly, Sarah Sachs, Brian Yin, Crystal Lee, Philipp Krähenbühl, Alexei A. Efros:
A Century of Portraits: A Visual Historical Record of American High School Yearbooks. IEEE Trans. Computational Imaging 3(3): 421-431 (2017) - [c15]R. Manmatha, Chao-Yuan Wu, Alexander J. Smola, Philipp Krähenbühl:
Sampling Matters in Deep Embedding Learning. ICCV 2017: 2859-2867 - [c14]Jeff Donahue, Philipp Krähenbühl, Trevor Darrell:
Adversarial Feature Learning. ICLR (Poster) 2017 - [i11]Chao-Yuan Wu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl:
Sampling Matters in Deep Embedding Learning. CoRR abs/1706.07567 (2017) - [i10]Chao-Yuan Wu, Manzil Zaheer, Hexiang Hu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl:
Compressed Video Action Recognition. CoRR abs/1712.00636 (2017) - 2016
- [c13]Tinghui Zhou, Philipp Krähenbühl, Mathieu Aubry, Qi-Xing Huang, Alexei A. Efros
Learning Dense Correspondence via 3D-Guided Cycle Consistency. CVPR 2016: 117-126 - [c12]Deepak Pathak, Philipp Krähenbühl, Jeff Donahue, Trevor Darrell, Alexei A. Efros
Context Encoders: Feature Learning by Inpainting. CVPR 2016: 2536-2544 - [c11]Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros
Generative Visual Manipulation on the Natural Image Manifold. ECCV (5) 2016: 597-613 - [c10]Philipp Krähenbühl, Carl Doersch, Jeff Donahue, Trevor Darrell:
Data-dependent Initializations of Convolutional Neural Networks. ICLR (Poster) 2016 - [i9]Tinghui Zhou, Philipp Krähenbühl, Mathieu Aubry, Qixing Huang, Alexei A. Efros:
Learning Dense Correspondence via 3D-guided Cycle Consistency. CoRR abs/1604.05383 (2016) - [i8]Deepak Pathak, Philipp Krähenbühl, Jeff Donahue, Trevor Darrell, Alexei A. Efros:
Context Encoders: Feature Learning by Inpainting. CoRR abs/1604.07379 (2016) - [i7]Jeff Donahue, Philipp Krähenbühl, Trevor Darrell:
Adversarial Feature Learning. CoRR abs/1605.09782 (2016) - [i6]Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros:
Generative Visual Manipulation on the Natural Image Manifold. CoRR abs/1609.03552 (2016) - 2015
- [c9]Philipp Krähenbühl, Vladlen Koltun:
Learning to propose objects. CVPR 2015: 1574-1582 - [c8]Deepak Pathak, Philipp Krähenbühl, Trevor Darrell:
Constrained Convolutional Neural Networks for Weakly Supervised Segmentation. ICCV 2015: 1796-1804 - [c7]Tinghui Zhou, Philipp Krähenbühl, Alexei A. Efros
Learning Data-Driven Reflectance Priors for Intrinsic Image Decomposition. ICCV 2015: 3469-3477 - [c6]Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros
Learning a Discriminative Model for the Perception of Realism in Composite Images. ICCV 2015: 3943-3951 - [i5]Deepak Pathak, Philipp Krähenbühl, Trevor Darrell:
Constrained Convolutional Neural Networks for Weakly Supervised Segmentation. CoRR abs/1506.03648 (2015) - [i4]Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros:
Learning a Discriminative Model for the Perception of Realism in Composite Images. CoRR abs/1510.00477 (2015) - [i3]Tinghui Zhou, Philipp Krähenbühl, Alexei A. Efros:
Learning Data-driven Reflectance Priors for Intrinsic Image Decomposition. CoRR abs/1510.02413 (2015) - [i2]Deepak Pathak, Philipp Krähenbühl, Stella X. Yu, Trevor Darrell:
Constrained Structured Regression with Convolutional Neural Networks. CoRR abs/1511.07497 (2015) - 2014
- [b1]Philipp Krähenbühl:
Dense random fields. Stanford University, USA, 2014 - [c5]Philipp Krähenbühl, Vladlen Koltun:
Geodesic Object Proposals. ECCV (5) 2014: 725-739 - 2013
- [c4]Philipp Krähenbühl, Vladlen Koltun:
Parameter Learning and Convergent Inference for Dense Random Fields. ICML (3) 2013: 513-521 - 2012
- [c3]Federico Perazzi, Philipp Krähenbühl, Yael Pritch, Alexander Hornung:
Saliency filters: Contrast based filtering for salient region detection. CVPR 2012: 733-740 - [c2]Philipp Krähenbühl, Vladlen Koltun:
Efficient Nonlocal Regularization for Optical Flow. ECCV (1) 2012: 356-369 - [i1]Philipp Krähenbühl, Vladlen Koltun:
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials. CoRR abs/1210.5644 (2012) - 2011
- [c1]Philipp Krähenbühl, Vladlen Koltun:
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials. NIPS 2011: 109-117 - 2010
- [j2]Sergey Levine, Philipp Krähenbühl, Sebastian Thrun, Vladlen Koltun:
Gesture controllers. ACM Trans. Graph. 29(4): 124:1-124:11 (2010)
2000 – 2009
- 2009
- [j1]Philipp Krähenbühl, Manuel Lang, Alexander Hornung, Markus H. Gross
A system for retargeting of streaming video. ACM Trans. Graph. 28(5): 126 (2009)
Coauthor Index
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last updated on 2024-11-19 20:47 CET by the dblp team
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