Philipp Krähenbühl

Department of Computer Science
University of Texas at Austin
2317 Speedway
Austin, TX 78712-1757

email: philkr (at) cs.utexas.edu
CV, DBLP, Google Scholar, github

Research

I am an Assistant Professor in the Department of Computer Science at the University of Texas at Austin. I received my PhD in 2014 from the CS Department at Stanford University and then spent two wonderful years as a PostDoc at UC Berkeley.

My research interests lie in Computer Vision, Machine learning and Computer Graphics. I’m particularly interested in deep learning, as well as image segmentation and understanding.

Publications

2019
Learning by Cheating
Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl
CORL 2019
[pdf] [details] [code]
Monocular plan view networks for autonomous driving
Dequan Wang, Coline Devin, Qi-Zhi Cai, Philipp Krähenbühl, and Trevor Darrell
IROS 2019
[pdf] [details]
Long-Term Feature Banks for Detailed Video Understanding
Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krähenbühl, Ross Girshick
CVPR 2019
[pdf] [details] [supplement] [code]
Bottom-up Object Detection by Grouping Extreme and Center Points
Xingyi Zhou, Jiacheng Zhuo, Philipp Krähenbühl
CVPR 2019
[pdf] [details] [supplement] [code]
Joint Monocular 3D Vehicle Detection and Tracking
Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang, Ji Lin, Min Sun, Philipp Krähenbühl, Trevor Darrell, and Fisher Yu
ICCV 2019
[pdf] [details]
Does Computer Vision Matter for Action?
Brady Zhou, Philipp Krähenbühl, Vladlen Koltun
Science Robotics 2019
[pdf] [details] [code]
Don't let your Discriminator be fooled
Brady Zhou, Philipp Krähenbühl
ICLR 2019
[pdf] [details]
2018
Video Compression through Image Interpolation
Chao-Yuan Wu, Nayan Singhal and Philipp Krähenbühl
ECCV 2018
[pdf] [details]
Domain transfer through deep activation matching
Haoshuo Huang,Qixing Huang and Philipp Krähenbühl
ECCV 2018
[pdf] [details] [project]
Compressed Video Action Recognition
Chao-Yuan Wu,Manzil Zaheer,Hexiang Hu,R. Manmatha,Alexander J. Smola and Philipp Krähenbühl
CVPR 2018
[pdf] [details] [project] [code]
Free Supervision from Video Games
Philipp Krähenbühl
CVPR 2018
[pdf] [details] [project] [code]
2017
Sampling Matters in Deep Embedding Learning
Chao-Yuan Wu, R. Manmatha, Alexander J. Smola and Philipp Krähenbühl
ICCV 2017
[pdf] [details] [project] [code]
Adversarial Feature Learning
Jeff Donahue, Philipp Krähenbühl and Trevor Darrell
ICLR 2017
[pdf] [details] [code]
2016
Generative Visual Manipulationon the Natural Image Manifold
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, and Alexei A. Efros
ECCV 2016
[pdf] [details] [project] [code]
Context Encoders: Feature Learning by Inpainting
Deepak Pathak, Philipp Krähenbühl, Jeff Donahue, Trevor Darrell and Alyosha Efros
CVPR 2016
[pdf] [details] [project] [code]
Learning Dense Correspondence via 3D-guided Cycle Consistency
Tinghui Zhou, Philipp Krähenbühl, Mathieu Aubry, Qixing Huang and Alyosha Efros
CVPR 2016
[pdf] [details] [project]
Data-dependent initializations of convolutional neural networks
Philipp Krähenbühl, Carl Doersch, Jeff Donahue and Trevor Darrell
ICLR 2016
[pdf] [details] [code] [py-faster-rcnn training scripts]
2015
Learning a Discriminative Model for the Perception of Realism in Composite Images
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman and Alyosha Efros
ICCV 2015
[pdf] [details] [code]
Learning Data-driven Reflectance Priors for Intrinsic Image Decomposition
Tinghui Zhou, Philipp Krähenbühl and Alyosha Efros
ICCV 2015
[pdf] [details] [code]
Constrained Convolutional Neural Networks for Weakly Supervised Segmentation
Deepak Pathak, Philipp Krähenbühl and Trevor Darrell
ICCV 2015
[pdf] [details] [supplement] [code]
Learning to propose objects
Philipp Krähenbühl and Vladlen Koltun
CVPR 2015
[pdf] [details] [code]
2014
Geodesic Object Proposals
Philipp Krähenbühl and Vladlen Koltun
ECCV 2014
[pdf] [details] [code] [data]
2013
Parameter Learning and Convergent Inference for Dense Random Fields
Philipp Krähenbühl and Vladlen Koltun
ICML 2013
[pdf] [details] [project] [code]
2012
Efficient Nonlocal regularization for Optical Flow
Philipp Krähenbühl and Vladlen Koltun
ECCV 2012
[pdf] [details]
Saliency Filters: Contrast Based Filtering for Salient Region Detection
Federico Perazzi, Philipp Krähenbühl, Yael Pritch and Alexander Hornung
CVPR 2012
[pdf] [details] [project] [code]
2011
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials
Philipp Krähenbühl and Vladlen Koltun
NIPS 2011
[pdf] [details] [project] [code]
2010
Gesture Controllers
Sergey Levine, Philipp Krähenbühl, Sebastian Thrun, Vladlen Koltun
SIGGRAPH 2010
[pdf] [details]
2009
A system for retargeting of streaming video
Philipp Krähenbühl, Manuel Lang, Alexander Hornung and Markus Gross
SIGGRAPH Asia 2009
[pdf] [details]

Research group

PhD Students:

Undergraduates and MS:

Past undergraduates and MS:

Teaching

Joining my research group

UT CS or ECE students: I’d recomment you to take my graduate deep learning class (CS395T), and start working with me throught that class.

Prospective students: Please read about our graduate admissions process and state your interested in my research group in your statement of purpose. Please do not contact me directly. The statistics are not in your favor either. We have not yet admitted a single student to UTCS who contacted me directly.

About my last name

I’m well aware that my last name is not the easiest one to write or cite (and I saw it butchered a bunch of times over the years). So to make things easier just pick your document type below and copy the string:

Regular text

Krähenbühl

Latex & Bibtex

Kr\"ahenb\"uhl

HTML

Krähenbühl

If all the above fail, just use Kraehenbuehl.