A system for retargeting of streaming video. - Philipp Krähenbühl; Manuel Lang; Alexander Hornung; Markus H. Gross (ACM Trans. Graph., 2009)

Gesture controllers. - Sergey Levine; Philipp Krähenbühl; Sebastian Thrun; Vladlen Koltun (ACM Trans. Graph., 2010)

Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials. - Philipp Krähenbühl; Vladlen Koltun (NIPS, 2011)

Saliency filters: Contrast based filtering for salient region detection. - Federico Perazzi; Philipp Krähenbühl; Yael Pritch; Alexander Hornung (CVPR, 2012)

Efficient Nonlocal Regularization for Optical Flow. - Philipp Krähenbühl; Vladlen Koltun (ECCV (1), 2012)

Parameter Learning and Convergent Inference for Dense Random Fields. - Philipp Krähenbühl; Vladlen Koltun (ICML (3), 2013)

Geodesic Object Proposals. - Philipp Krähenbühl; Vladlen Koltun (ECCV (5), 2014)

Dense random fields. - Philipp Krähenbühl (2014)

Learning to propose objects. - Philipp Krähenbühl; Vladlen Koltun (CVPR, 2015)

Constrained Convolutional Neural Networks for Weakly Supervised Segmentation. - Deepak Pathak; Philipp Krähenbühl; Trevor Darrell (ICCV, 2015)

Learning Data-Driven Reflectance Priors for Intrinsic Image Decomposition. - Tinghui Zhou; Philipp Krähenbühl; Alexei A. Efros (ICCV, 2015)

Learning a Discriminative Model for the Perception of Realism in Composite Images. - Jun-Yan Zhu; Philipp Krähenbühl; Eli Shechtman; Alexei A. Efros (ICCV, 2015)

Constrained Structured Regression with Convolutional Neural Networks. - Deepak Pathak; Philipp Krähenbühl; Stella X. Yu; Trevor Darrell (CoRR, 2015)

Context Encoders: Feature Learning by Inpainting. - Deepak Pathak; Philipp Krähenbühl; Jeff Donahue; Trevor Darrell; Alexei A. Efros (CVPR, 2016)

Learning Dense Correspondence via 3D-Guided Cycle Consistency. - Tinghui Zhou; Philipp Krähenbühl; Mathieu Aubry; Qi-Xing Huang; Alexei A. Efros (CVPR, 2016)

Generative Visual Manipulation on the Natural Image Manifold. - Jun-Yan Zhu; Philipp Krähenbühl; Eli Shechtman; Alexei A. Efros (ECCV (5), 2016)

Data-dependent Initializations of Convolutional Neural Networks. - Philipp Krähenbühl; Carl Doersch; Jeff Donahue; Trevor Darrell (ICLR (Poster), 2016)

Sampling Matters in Deep Embedding Learning. - R. Manmatha; Chao-Yuan Wu; Alexander J. Smola; Philipp Krähenbühl (ICCV, 2017)

Adversarial Feature Learning. - Jeff Donahue; Philipp Krähenbühl; Trevor Darrell (ICLR (Poster), 2017)

A Century of Portraits: A Visual Historical Record of American High School Yearbooks. - Shiry Ginosar; Kate Rakelly; Sarah Sachs; Brian Yin; Crystal Lee; Philipp Krähenbühl; Alexei A. Efros (IEEE Trans. Computational Imaging, 2017)

Free Supervision From Video Games. - Philipp Krähenbühl (CVPR, 2018)

Compressed Video Action Recognition. - Chao-Yuan Wu; Manzil Zaheer; Hexiang Hu; R. Manmatha; Alexander J. Smola; Philipp Krähenbühl (CVPR, 2018)

Domain Transfer Through Deep Activation Matching. - Haoshuo Huang; Qixing Huang; Philipp Krähenbühl (ECCV (16), 2018)

Video Compression Through Image Interpolation. - Chao-Yuan Wu; Nayan Singhal; Philipp Krähenbühl (ECCV (8), 2018)

Assessing Generalization in Deep Reinforcement Learning. - Charles Packer; Katelyn Gao; Jernej Kos; Philipp Krähenbühl; Vladlen Koltun; Dawn Song (CoRR, 2018)

Learning by Cheating. - Dian Chen 001; Brady Zhou; Vladlen Koltun; Philipp Krähenbühl (CoRL, 2019)

Long-Term Feature Banks for Detailed Video Understanding. - Chao-Yuan Wu; Christoph Feichtenhofer; Haoqi Fan 001; Kaiming He; Philipp Krähenbühl; Ross B. Girshick (CVPR, 2019)

Bottom-Up Object Detection by Grouping Extreme and Center Points. - Xingyi Zhou; Jiacheng Zhuo; Philipp Krähenbühl (CVPR, 2019)

Joint Monocular 3D Vehicle Detection and Tracking. - Hou-Ning Hu; Qi-Zhi Cai; Dequan Wang; Ji Lin 002; Min Sun 001; Philipp Krähenbühl; Trevor Darrell; Fisher Yu 001 (ICCV, 2019)

Don't let your Discriminator be fooled. - Brady Zhou; Philipp Krähenbühl (ICLR (Poster), 2019)

Monocular Plan View Networks for Autonomous Driving. - Dequan Wang; Coline Devin; Qi-Zhi Cai; Philipp Krähenbühl; Trevor Darrell (IROS, 2019)

Objects as Points. - Xingyi Zhou; Dequan Wang; Philipp Krähenbühl (CoRR, 2019)

Does computer vision matter for action? - Brady Zhou; Philipp Krähenbühl; Vladlen Koltun (Sci. Robotics, 2019)

A Multigrid Method for Efficiently Training Video Models. - Chao-Yuan Wu; Ross B. Girshick; Kaiming He; Christoph Feichtenhofer; Philipp Krähenbühl (CVPR, 2020)

Tracking Objects as Points. - Xingyi Zhou; Vladlen Koltun; Philipp Krähenbühl (ECCV (4), 2020)

Domain Adaptation Through Task Distillation. - Brady Zhou; Nimit Kalra; Philipp Krähenbühl (ECCV (26), 2020)

Lossless Image Compression through Super-Resolution. - Sheng Cao; Chao-Yuan Wu; Philipp Krähenbühl (CoRR, 2020)

Towards Long-Form Video Understanding. - Chao-Yuan Wu; Philipp Krähenbühl (CVPR, 2021)

Center-Based 3D Object Detection and Tracking. - Tianwei Yin; Xingyi Zhou; Philipp Krähenbühl (CVPR, 2021)

Learning to drive from a world on rails. - Dian Chen 001; Vladlen Koltun; Philipp Krähenbühl (ICCV, 2021)

Memory Optimization for Deep Networks. - Aashaka Shah; Chao-Yuan Wu; Jayashree Mohan; Vijay Chidambaram; Philipp Krähenbühl (ICLR, 2021)

Multimodal Virtual Point 3D Detection. - Tianwei Yin; Xingyi Zhou; Philipp Krähenbühl (NeurIPS, 2021)

Probabilistic two-stage detection. - Xingyi Zhou; Vladlen Koltun; Philipp Krähenbühl (CoRR, 2021)

Learning from All Vehicles. - Dian Chen 001; Philipp Krähenbühl (CVPR, 2022)

Cross-view Transformers for real-time Map-view Semantic Segmentation. - Brady Zhou; Philipp Krähenbühl (CVPR, 2022)

Simple Multi-dataset Detection. - Xingyi Zhou; Vladlen Koltun; Philipp Krähenbühl (CVPR, 2022)

Global Tracking Transformers. - Xingyi Zhou; Tianwei Yin; Vladlen Koltun; Philipp Krähenbühl (CVPR, 2022)

Long-tail Detection with Effective Class-Margins. - Jang Hyun Cho; Philipp Krähenbühl (ECCV (8), 2022)

Real-Time Online Video Detection with Temporal Smoothing Transformers. - Yue Zhao 006; Philipp Krähenbühl (ECCV (34), 2022)

Detecting Twenty-Thousand Classes Using Image-Level Supervision. - Xingyi Zhou; Rohit Girdhar; Armand Joulin; Philipp Krähenbühl; Ishan Misra (ECCV (9), 2022)

NMS Strikes Back. - Jeffrey Ouyang-Zhang; Jang Hyun Cho; Xingyi Zhou; Philipp Krähenbühl (CoRR, 2022)

Language Conditioned Traffic Generation. - Shuhan Tan; Boris Ivanovic; Xinshuo Weng; Marco Pavone 001; Philipp Krähenbühl (CoRL, 2023)

Learning Video Representations from Large Language Models. - Yue Zhao 006; Ishan Misra; Philipp Krähenbühl; Rohit Girdhar (CVPR, 2023)

PartDistillation: Learning Parts from Instance Segmentation. - Jang Hyun Cho; Philipp Krähenbühl; Vignesh Ramanathan (CVPR, 2023)

Predicting a Protein's Stability under a Million Mutations. - Jeffrey Ouyang-Zhang; Daniel Jesus Diaz; Adam R. Klivans; Philipp Krähenbühl (NeurIPS, 2023)

Training a Large Video Model on a Single Machine in a Day. - Yue Zhao 006; Philipp Krähenbühl (CoRR, 2023)

Promptable Closed-loop Traffic Simulation. - Shuhan Tan; Boris Ivanovic; Yuxiao Chen 008; Boyi Li; Xinshuo Weng; Yulong Cao; Philipp Krähenbühl; Marco Pavone 001 (CoRL, 2024)

Distilling Vision-Language Models on Millions of Videos. - Yue Zhao 006; Long Zhao 003; Xingyi Zhou; Jialin Wu; Chun-Te Chu; Hui Miao; Florian Schroff; Hartwig Adam; Ting Liu 005; Boqing Gong; Philipp Krähenbühl; Liangzhe Yuan (CVPR, 2024)

Language-Conditioned Detection Transformer. - Jang Hyun Cho; Philipp Krähenbühl (CVPR, 2024)

Image and Video Tokenization with Binary Spherical Quantization. - Yue Zhao 006; Yuanjun Xiong; Philipp Krähenbühl (ICLR, 2025)

Language-Image Models with 3D Understanding. - Jang Hyun Cho; Boris Ivanovic; Yulong Cao; Edward Schmerling; Yue Wang 041; Xinshuo Weng; Boyi Li; Yurong You; Philipp Krähenbühl; Yan Wang 051; Marco Pavone 001 (ICLR, 2025)

Distilling Structural Representations into Protein Sequence Models. - Jeffrey Ouyang-Zhang; Chengyue Gong; Yue Zhao 006; Philipp Krähenbühl; Adam R. Klivans; Daniel Jesus Diaz (ICLR, 2025)

Does Spatial Cognition Emerge in Frontier Models? - Santhosh Kumar Ramakrishnan; Erik Wijmans; Philipp Krähenbühl; Vladlen Koltun (ICLR, 2025)

Cut Your Losses in Large-Vocabulary Language Models. - Erik Wijmans; Brody Huval; Alexander Hertzberg; Vladlen Koltun; Philipp Krähenbühl (ICLR, 2025)

Reinforcement Learning for Long-Horizon Interactive LLM Agents. - Kevin Chen; Marco F. Cusumano-Towner; Brody Huval; Aleksei Petrenko; Jackson Hamburger; Vladlen Koltun; Philipp Krähenbühl (CoRR, 2025)

Robust Autonomy Emerges from Self-Play. - Marco F. Cusumano-Towner; David Hafner; Alexander Hertzberg; Brody Huval; Aleksei Petrenko; Eugene Vinitsky; Erik Wijmans; Taylor Killian; Stuart Bowers; Ozan Sener; Philipp Krähenbühl; Vladlen Koltun (CoRR, 2025)

QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation. - Yue Zhao 006; Fuzhao Xue; Scott Reed; Linxi Fan; Yuke Zhu; Jan Kautz; Zhiding Yu; Philipp Krähenbühl; De-An Huang (CoRR, 2025)

PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding. - Jang Hyun Cho; Andrea Madotto; Effrosyni Mavroudi; Triantafyllos Afouras; Tushar Nagarajan; Muhammad Maaz 001; Yale Song; Tengyu Ma 005; Shuming Hu; Suyog Dutt Jain; Miguel Martin; Huiyu Wang; et al. (CoRR, 2025)

Interactive Post-Training for Vision-Language-Action Models. - Shuhan Tan; Kairan Dou; Yue Zhao 006; Philipp Krähenbühl (CoRR, 2025)

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation. - Xiuyu Yang; Shuhan Tan; Philipp Krähenbühl (CoRR, 2025)