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

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] [slides] [code]
Learning Data-driven Reflectance Priors for Intrinsic Image Decomposition
Tinghui Zhou, Philipp Krähenbühl and Alyosha Efros
ICCV 2015
[pdf] [details] [slides] [code]
Constrained Convolutional Neural Networks for Weakly Supervised Segmentation
Deepak Pathak, Philipp Krähenbühl and Trevor Darrell
ICCV 2015
[pdf] [details] [supplement] [slides] [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 (oral)
[pdf] [details] [slides] [poster] [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 (best student paper)
[pdf] [details] [project] [code]
2010
Gesture Controllers
Sergey Levine, Philipp Krähenbühl, Sebastian Thrun, Vladlen Koltun
SIGGRAPH 2010
[pdf] [details]
2009
Retargeting of Streaming Video
Philipp Krähenbühl, Manuel Lang, Alexander Hornung and Markus Gross
SIGGRAPH Asia 2009
[pdf] [details]

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 insterested in my research group in your statement of purpose. It is not necessary to contact 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.