Philipp Krähenbühl

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Vladlen KoltunDistinguished Scientist, AppleVerified email at apple.com
Xingyi ZhouGoogle DeepMindVerified email at utexas.edu
Trevor DarrellProfessor of Computer Science, U.C. BerkeleyVerified email at eecs.berkeley.edu
Alexei A. EfrosDept. of Electrical Engineering and Computer Sciences, UC BerkeleyVerified email at eecs.berkeley.edu
Chao-Yuan WuWorld LabsVerified email at meta.com
Jeff DonahueResearch Scientist, DeepMindVerified email at google.com
Dequan WangShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Alexander Sorkine-HornungMetaVerified email at sorkine-hornung.com
Deepak PathakAssistant Professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Yael PritchGoogle ResearchVerified email at google.com
Federico PerazziBending SpoonsVerified email at bendingspoons.com
Tianwei YinMITVerified email at mit.edu
Brady ZhouUT AustinVerified email at utexas.edu
Eli ShechtmanSenior Principal Scientist, Adobe ResearchVerified email at adobe.com
Jun-Yan ZhuAssistant Professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Alex SmolaBoson AIVerified email at smola.org
R. ManmathaA9/AmazonVerified email at cs.umass.edu
Dian ChenWaabiVerified email at waabi.ai
Yue ZhaoUniversity of Texas at AustinVerified email at cs.utexas.edu
Markus GrossETH Zurich, Disney Research ZurichVerified email at inf.ethz.ch

Philipp Krähenbühl

UT Austin

Verified email at cs.utexas.edu - Homepage

Computer Vision Machine Learning Computer Graphics


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Context encoders: Feature learning by inpainting D Pathak, P Krahenbuhl, J Donahue, T Darrell, AA Efros Proceedings of the IEEE conference on computer vision and pattern …, 2016	6951	2016
Objects as points X Zhou, D Wang, P Krähenbühl arXiv preprint arXiv:1904.07850, 2019	4679	2019
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials P Krähenbühl, V Koltun NIPS, 2011	4210	2011
Adversarial feature learning J Donahue, P Krähenbühl, T Darrell arXiv preprint arXiv:1605.09782, 2016	2652	2016
Saliency filters: Contrast based filtering for salient region detection F Perazzi, P Krähenbühl, Y Pritch, A Hornung 2012 IEEE conference on computer vision and pattern recognition, 733-740, 2012	2462	2012
Center-based 3d object detection and tracking T Yin, X Zhou, P Krähenbühl CVPR, 2021	1956	2021
Generative visual manipulation on the natural image manifold JY Zhu, P Krähenbühl, E Shechtman, AA Efros Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016	1687	2016
Tracking Objects as Points X Zhou, V Koltun, P Krähenbühl ECCV, 2020	1370	2020
Bottom-up object detection by grouping extreme and center points X Zhou, J Zhuo, P Krahenbuhl Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019	1216	2019
Sampling matters in deep embedding learning CY Wu, R Manmatha, AJ Smola, P Krähenbühl ICCV 2017, 2017	1151	2017
Constrained convolutional neural networks for weakly supervised segmentation D Pathak, P Krahenbuhl, T Darrell Proceedings of the IEEE international conference on computer vision, 1796-1804, 2015	788	2015
Detecting twenty-thousand classes using image-level supervision X Zhou, R Girdhar, A Joulin, P Krähenbühl, I Misra European Conference on Computer Vision, 350-368, 2022	644	2022
Long-term feature banks for detailed video understanding CY Wu, C Feichtenhofer, H Fan, K He, P Krahenbuhl, R Girshick Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019	602	2019
Learning by cheating D Chen, B Zhou, V Koltun, P Krähenbühl Conference on Robot Learning, 66-75, 2019	546	2019
Geodesic object proposals P Krähenbühl, V Koltun Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014	475	2014
Learning dense correspondence via 3d-guided cycle consistency T Zhou, P Krahenbuhl, M Aubry, Q Huang, AA Efros Proceedings of the IEEE conference on computer vision and pattern …, 2016	446	2016
Compressed video action recognition CY Wu, M Zaheer, H Hu, R Manmatha, AJ Smola, P Krähenbühl Proceedings of the IEEE conference on computer vision and pattern …, 2018	416	2018
Video compression through image interpolation CY Wu, N Singhal, P Krahenbuhl Proceedings of the European conference on computer vision (ECCV), 416-431, 2018	404	2018
Probabilistic two-stage detection X Zhou, V Koltun, P Krähenbühl arXiv preprint arXiv:2103.07461, 2021	319	2021
A system for retargeting of streaming video P Krähenbühl, M Lang, A Hornung, M Gross ACM SIGGRAPH Asia 2009 papers, 1-10, 2009	310	2009

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