Christoph Feichtenhofer
Christoph Feichtenhofer
Research Scientist, Facebook AI Research (FAIR)
Verified email at fb.com - Homepage
Title
Cited by
Cited by
Year
Convolutional two-stream network fusion for video action recognition
C Feichtenhofer, A Pinz, AP Zisserman
Computer Vision and Pattern Recognition (CVPR), 2016, 2016
22852016
SlowFast Networks for Video Recognition
C Feichtenhofer, H Fan, J Malik, K He
International Conference on Computer Vision (ICCV), 2019, 2019
10062019
Spatiotemporal multiplier networks for video action recognition
C Feichtenhofer, A Pinz, RP Wildes
Proceedings of the IEEE conference on computer vision and pattern …, 2017
8512017
3d human pose estimation in video with temporal convolutions and semi-supervised training
D Pavllo, C Feichtenhofer, D Grangier, M Auli
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
4102019
Detect to track and track to detect
C Feichtenhofer, A Pinz, A Zisserman
Proceedings of the IEEE International Conference on Computer Vision, 3038-3046, 2017
4042017
Long-term feature banks for detailed video understanding
CY Wu, C Feichtenhofer, H Fan, K He, P Krahenbuhl, R Girshick
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
2632019
X3D: Expanding architectures for efficient video recognition
C Feichtenhofer
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
2092020
A perceptual image sharpness metric based on local edge gradient analysis
C Feichtenhofer, H Fassold, P Schallauer
IEEE Signal Processing Letters 20 (4), 379-382, 2013
932013
Modeling human motion with quaternion-based neural networks
D Pavllo, C Feichtenhofer, M Auli, D Grangier
International Journal of Computer Vision, 1-18, 2019
832019
Temporal Residual Networks for Dynamic Scene Recognition
C Feichtenhofer, A Pinz, RP Wildes
Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on, 2017
752017
Multiscale Vision Transformers
H Fan, B Xiong, K Mangalam, Y Li, Z Yan, J Malik, C Feichtenhofer
arXiv preprint arXiv:2104.11227, 2021
672021
Audiovisual slowfast networks for video recognition
F Xiao, YJ Lee, K Grauman, J Malik, C Feichtenhofer
arXiv preprint arXiv:2001.08740, 2020
672020
Bags of Spacetime Energies for Dynamic Scene Recognition
C Feichtenhofer, A Pinz, RP Wildes
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, 2014
672014
Trackformer: Multi-object tracking with transformers
T Meinhardt, A Kirillov, L Leal-Taixe, C Feichtenhofer
arXiv preprint arXiv:2101.02702, 2021
642021
A multigrid method for efficiently training video models
CY Wu, R Girshick, K He, C Feichtenhofer, P Krahenbuhl
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
572020
What have we learned from deep representations for action recognition?
C Feichtenhofer, A Pinz, RP Wildes, A Zisserman
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
452018
Grounded human-object interaction hotspots from video
T Nagarajan, C Feichtenhofer, K Grauman
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
412019
Spacetime Forests with Complementary Features for Dynamic Scene Recognition.
C Feichtenhofer, A Pinz, RP Wildes
BMVC, 6, 2013
412013
A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning
C Feichtenhofer, H Fan, B Xiong, R Girshick, K He
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
352021
Ego-topo: Environment affordances from egocentric video
T Nagarajan, Y Li, C Feichtenhofer, K Grauman
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
342020
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