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Group convolution has been shown to offer great computational savings in various 2D convolutional architectures for image classification.
Space-time interest points
Ivan Laptev and Tony Lindeberg · 2003
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Behavior recognition via sparse spatio-temporal features
Piotr Dollar, Vincent Rabaud, Garrison Cottrell, and Serge Belongie · 2005
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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Action bank: A high-level representation of activity in video
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Action recognition with improved trajectories
Heng Wang and Cordelia Schmid · 2013
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Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, and Li Fei-Fei · 2014
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Two-stream convolutional networks for action recognition in videos
Karen Simonyan and Andrew Zisserman · 2014
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Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri · 2015
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Beyond short snippets: Deep networks for video classification
Joe Yue-Hei Ng, Matthew Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, and George Toderici · 2015
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Spatiotemporal residual networks for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Richard P. Wildes · 2016
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Convolutional two-stream network fusion for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Andrew Zisserman · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Temporal segment networks: Towards good practices for deep action recognition
Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao, Dahua Lin, Xiaoou Tang, and Luc Van Gool · 2016
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Actions ~ transformations
Xiaolong Wang, Ali Farhadi, and Abhinav Gupta · 2016
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Yunlong Bian, Chuang Gan, Xiao Liu, Fu Li, Xiang Long, Yandong Li, Heng Qi, Jie Zhou, Shilei Wen, and Yuanqing Lin · 2017
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Joao Carreira and Andrew Zisserman · 2017
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Xception: Deep learning with depthwise separable convolutions
François Chollet · 2017
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Accurate, large minibatch sgd: training imagenet in 1 hour
Priya Goyal, Piotr Dollár, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He · 2017
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Motion feature network: Fixed motion filter for action recognition
Myunggi Lee, Seungeui Lee, Sungjoon Son, Gyutae Park, and Nojun Kwak · 2018
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Temporal shift module for efficient video understanding
Ji Lin, Chuang Gan, and Song Han · 2018
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Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
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D3D: distilled 3d networks for video action recognition
Jonathan C. Stroud, David A. Ross, Chen Sun, Jia Deng, and Rahul Sukthankar · 2018
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A closer look at spatiotemporal convolutions for action recognition
Du Tran, Heng Wang, Lorenzo Torresani, Jamie Ray, Yann LeCun, and Manohar Paluri · 2018
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The kinetics human action video dataset
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Multi-fiber networks for video recognition
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Appearance-and-relation networks for video classification
Limin Wang, Wei Li, Wen Li, and Luc Van Gool · 2018
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Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
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Videos as space-time region graphs
Xiaolong Wang and Abhinav Gupta · 2018
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Rethinking spatiotemporal feature learning for video understanding
Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy · 2018
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Temporal relational reasoning in videos
Bolei Zhou, Alex Andonian, and Antonio Torralba · 2018
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ECO: Efficient convolutional network for online video understanding
Mohammadreza Zolfaghari, Kamaljeet Singh, and Thomas Brox · 2018
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Graph-based global reasoning networks
Yunpeng Chen, Marcus Rohrbach, Zhicheng Yan, Shuicheng Yan, Jiashi Feng, and Yannis Kalantidis · 2019
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Slowfast networks for video recognition
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He · 2019
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Large-scale weakly-supervised pre-training for video action recognition
Deepti Ghadiyaram, Matt Feiszli, Du Tran, Xueting Yan, Heng Wang, and Dhruv Mahajan · 2019
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