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Learning to represent videos is a very challenging task both algorithmically and computationally.
Convolutional two-stream network fusion for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Andrew Zisserman · 1941
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A comparative analysis of selection schemes used in genetic algorithms
David E. Goldberg and Kalyanmoy Deb · 1991
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A duality based approach for realtime tv-l 1 optical flow
Christopher Zach, Thomas Pock, and Horst Bischof · 2007
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Two-stream convolutional networks for action recognition in videos
Karen Simonyan and Andrew Zisserman · 2014
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C3d: generic features for video analysis
Du Tran, Lubomir D Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Hollywood in homes: Crowdsourcing data collection for activity understanding
Gunnar A. Sigurdsson, Gül Varol, Xiaolong Wang, Ali Farhadi, Ivan Laptev, and Abhinav Gupta · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 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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Multi-scale context aggregation by dilated convolutions
Fisher Yu and Vladlen Koltun · 2016
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Connectivity learning in multi-branch networks
Karim Ahmed and Lorenzo Torresani · 2017
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Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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Spatiotemporal multiplier networks for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Richard P Wildes · 2017
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Temporal convolutional networks for action segmentation and detection
Colin Lea, Michael D. Flynn, Rene Vidal, Austin Reiter, and Gregory D. Hager · 2017
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Asynchronous temporal fields for action recognition
Gunnar A Sigurdsson, Santosh Divvala, Ali Farhadi, and Abhinav Gupta · 2017
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Neural architecture search with reinforcement learning
Barret Zoph and Quoc Le · 2017
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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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Videos as space-time region graphs
Xiaolong Wang and Abhinav Gupta · 2018
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Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
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Rethinking spatiotemporal feature learning: Speed-accuracy trade-offs in video classification
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, Aude Oliva, and Antonio Torralba · 2018
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Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V. Le · 2018
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Holistic large scale video understanding
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