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Center-based 3D Object Detection and Tracking

Jun 19, 2020
Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl


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Lossless Image Compression through Super-Resolution

Apr 06, 2020
Sheng Cao, Chao-Yuan Wu, Philipp Krähenbühl

* Tech report 

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Tracking Objects as Points

Apr 02, 2020
Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl

* Code available at https://github.com/xingyizhou/CenterTrack 

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Learning by Cheating

Dec 27, 2019
Dian Chen, Brady Zhou, Vladlen Koltun, Philipp Krähenbühl

* Paper published in CoRL2019 

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A Multigrid Method for Efficiently Training Video Models

Dec 02, 2019
Chao-Yuan Wu, Ross Girshick, Kaiming He, Christoph Feichtenhofer, Philipp Krähenbühl

* Technical report 

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Does computer vision matter for action?

May 30, 2019
Brady Zhou, Philipp Krähenbühl, Vladlen Koltun

* Science Robotics 22 May 2019: Vol. 4, Issue 30, eaaw6661 
* Published in Science Robotics, 4(30), May 2019 

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Monocular Plan View Networks for Autonomous Driving

May 16, 2019
Dequan Wang, Coline Devin, Qi-Zhi Cai, Philipp Krähenbühl, Trevor Darrell

* 8 pages, 9 figures 

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Objects as Points

Apr 25, 2019
Xingyi Zhou, Dequan Wang, Philipp Krähenbühl

* 12 pages, 5 figures 

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Bottom-up Object Detection by Grouping Extreme and Center Points

Feb 03, 2019
Xingyi Zhou, Jiacheng Zhuo, Philipp Krähenbühl


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Long-Term Feature Banks for Detailed Video Understanding

Dec 12, 2018
Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krähenbühl, Ross Girshick

* Technical report 

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Joint Monocular 3D Vehicle Detection and Tracking

Dec 02, 2018
Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang, Ji Lin, Min Sun, Philipp Krähenbühl, Trevor Darrell, Fisher Yu

* 14 pages, 11 figures. Fix table values misplacement and typos. All the results unchanged 

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Assessing Generalization in Deep Reinforcement Learning

Oct 29, 2018
Charles Packer, Katelyn Gao, Jernej Kos, Philipp Krähenbühl, Vladlen Koltun, Dawn Song

* 18 pages, 6 figures 

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Video Compression through Image Interpolation

Apr 18, 2018
Chao-Yuan Wu, Nayan Singhal, Philipp Krähenbühl

* Project page: https://chaoyuaw.github.io/vcii/ 

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Compressed Video Action Recognition

Mar 29, 2018
Chao-Yuan Wu, Manzil Zaheer, Hexiang Hu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl

* CVPR 2018 (Selected for spotlight presentation) 

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Sampling Matters in Deep Embedding Learning

Jan 16, 2018
Chao-Yuan Wu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl

* Add supplementary material. Paper published in ICCV 2017 

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Adversarial Feature Learning

Apr 03, 2017
Jeff Donahue, Philipp Krähenbühl, Trevor Darrell

* Published as a conference paper at ICLR 2017. Changelog: (v7) Table 2 results improved 1-2% due to averaging predictions over 10 crops at test time, as done in Noroozi & Favaro; Table 3 VOC classification results slightly improved due to minor bugfix. (See v6 changelog for previous versions.) 

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Generative Visual Manipulation on the Natural Image Manifold

Sep 25, 2016
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros

* In European Conference on Computer Vision (ECCV 2016) 

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Data-dependent Initializations of Convolutional Neural Networks

Sep 22, 2016
Philipp Krähenbühl, Carl Doersch, Jeff Donahue, Trevor Darrell

* ICLR 2016 

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Learning Dense Correspondence via 3D-guided Cycle Consistency

Apr 18, 2016
Tinghui Zhou, Philipp Krähenbühl, Mathieu Aubry, Qixing Huang, Alexei A. Efros

* To appear in CVPR 2016 (oral presentation) 

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Constrained Structured Regression with Convolutional Neural Networks

Nov 23, 2015
Deepak Pathak, Philipp Krähenbühl, Stella X. Yu, Trevor Darrell


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Constrained Convolutional Neural Networks for Weakly Supervised Segmentation

Oct 18, 2015
Deepak Pathak, Philipp Krähenbühl, Trevor Darrell

* 12 pages, ICCV 2015 

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Learning Data-driven Reflectance Priors for Intrinsic Image Decomposition

Oct 08, 2015
Tinghui Zhou, Philipp Krähenbühl, Alexei A. Efros

* International Conference on Computer Vision (ICCV) 2015 

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Learning a Discriminative Model for the Perception of Realism in Composite Images

Oct 02, 2015
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros

* International Conference on Computer Vision (ICCV) 2015 

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Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials

Oct 20, 2012
Philipp Krähenbühl, Vladlen Koltun

* Advances in Neural Information Processing Systems 24 (2011) 109-117 
* NIPS 2011 

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