I am a research scientist at Facebook AI Research (FAIR). Prior to joining Facebook in Spring 2018, I received the PhD degree in computer science from TU Graz, and spent time as a visiting researcher at the York University Toronto and the University of Oxford. I am the recipient of a DOC Fellowship of the Austrian Academy of Sciences and my PhD thesis was awarded with the Award of Excellence for outstanding doctoral theses in Austria. My main areas of research include the development of effective representations for video understanding. I aim to find solutions for problems that are grounded in applications such as recognition and detection from video.
Interests
Computer vision and deep learning
Latest Publications
CVPR - June 16, 2020
A Multigrid Method for Efficiently Training Video Models
Chao-Yuan Wu, Ross Girshick, Kaiming He, Christoph Feichtenhofer, Philipp Krähenbühl
CVPR - June 14, 2020
EGO-TOPO: Environment Affordances from Egocentric Video
Tushar Nagarajan, Yanghao Li, Christoph Feichtenhofer, Kristen Grauman
CVPR - June 9, 2020
X3D: Expanding Architectures for Efficient Video Recognition
Christoph Feichtenhofer
ICCV - October 28, 2019
SlowFast Networks for Video Recognition
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, Kaiming He
NeurIPS - October 27, 2019
Learning Temporal Pose Estimation from Sparsely-Labeled Videos
Gedas Bertasius, Christoph Feichtenhofer, Du Tran, Jianbo Shi, Lorenzo Torresani
ICCV - October 26, 2019
Grounded Human-Object Interaction Hotspots From Video
Tushar Nagarajan, Christoph Feichtenhofer, Kristen Grauman
CVPR - June 18, 2019
Long-Term Feature Banks for Detailed Video Understanding
Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krähenbühl, Ross Girshick
CVPR - June 16, 2019
3D human pose estimation in video with temporal convolutions and semi-supervised training
Dario Pavllo, Christoph Feichtenhofer, David Grangier, Michael Auli
Videos
All Videos
EGO-TOPO: Environment Affordances from Egocentric Video
| June 9, 2020