Philipp Krähenbühl
Philipp Krähenbühl
Verified email at cs.utexas.edu - Homepage
Title
Cited by
Cited by
Year
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials
P Krähenbühl, V Koltun
NIPS, 2011
20612011
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
17192016
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
13262012
Adversarial feature learning
J Donahue, P Krähenbühl, T Darrell
arXiv preprint arXiv:1605.09782, 2016
7952016
Generative visual manipulation on the natural image manifold
JY Zhu, P Krähenbühl, E Shechtman, AA Efros
European Conference on Computer Vision, 597-613, 2016
6622016
Geodesic object proposals
P Krähenbühl, V Koltun
European conference on computer vision, 725-739, 2014
3652014
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
3502015
A system for retargeting of streaming video
P Krähenbühl, M Lang, A Hornung, M Gross
ACM SIGGRAPH Asia 2009 papers, 1-10, 2009
2542009
Sampling matters in deep embedding learning
CY Wu, R Manmatha, AJ Smola, P Krähenbühl
ICCV 2017, 2017
2452017
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
1782016
Parameter learning and convergent inference for dense random fields
P Krähenbühl, V Koltun
International Conference on Machine Learning, 513-521, 2013
1762013
SWPS3–fast multi-threaded vectorized Smith-Waterman for IBM Cell/BE and× 86/SSE2
A Szalkowski, C Ledergerber, P Krähenbühl, C Dessimoz
BMC research notes 1 (1), 107, 2008
1382008
Data-dependent initializations of convolutional neural networks
P Krähenbühl, C Doersch, J Donahue, T Darrell
arXiv preprint arXiv:1511.06856, 2015
1372015
Objects as points
X Zhou, D Wang, P Krähenbühl
arXiv preprint arXiv:1904.07850, 2019
1272019
Gesture controllers
S Levine, P Krähenbühl, S Thrun, V Koltun
ACM SIGGRAPH 2010 papers, 1-11, 2010
1042010
Bottom-up object detection by grouping extreme and center points
X Zhou, J Zhuo, P Krahenbuhl
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
972019
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
922018
Learning data-driven reflectance priors for intrinsic image decomposition
T Zhou, P Krahenbuhl, AA Efros
Proceedings of the IEEE International Conference on Computer Vision, 3469-3477, 2015
922015
Learning to Propose Objects
P Krähenbühl, V Koltun
Computer Vision and Pattern Recognition (CVPR), 2015
782015
Long-term feature banks for detailed video understanding
CY Wu, C Feichtenhofer, H Fan, K He, P Krahenbuhl, R Girshick
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
582019
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