Fetching the paper…
Reading the bibliography…
Most action recognition solutions rely on dense sampling to precisely cover the informative temporal clip.
Convolutional learning of spatio-temporal features
Graham W Taylor, Rob Fergus, Yann LeCun, and Christoph Bregler · 2010
Earlier work this paper cites.
Less is more: trading a little bandwidth for ultra-low latency in the data center
Mohammad Alizadeh, Abdul Kabbani, Tom Edsall, Balaji Prabhakar, Amin Vahdat, and Masato Yasuda · 2012
Earlier work this paper cites.
A dataset of 101 human action classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
Earlier work this paper cites.
Diverse sequential subset selection for supervised video summarization
Boqing Gong, Wei-Lun Chao, Kristen Grauman, and Fei Sha · 2014
Earlier work this paper cites.
Action localization with tubelets from motion
Mihir Jain, Jan Van Gemert, Hervé Jégou, Patrick Bouthemy, and Cees GM Snoek · 2014
Earlier work this paper cites.
Large-scale video classification with convolutional neural networks
Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, and Li Fei-Fei · 2014
Earlier work this paper cites.
Activitynet: A large-scale video benchmark for human activity understanding
Bernard Ghanem Fabian Caba Heilbron, Victor Escorcia and Juan Carlos Niebles · 2015
Earlier work this paper cites.
Learning spatiotemporal features with 3d convolutional networks
Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri · 2015
Earlier work this paper cites.
Actionness estimation using hybrid fully convolutional networks
Limin Wang, Yu Qiao, Xiaoou Tang, and Luc Van Gool · 2016
Earlier work this paper cites.
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
Earlier work this paper cites.
Real-time action recognition with enhanced motion vector cnns
Bowen Zhang, Limin Wang, Zhe Wang, Yu Qiao, and Hanli Wang · 2016
Earlier work this paper cites.
Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
Earlier work this paper cites.
Temporal perceptive network for skeleton-based action recognition
Yueyu Hu, Chunhui Liu, Yanghao Li, and Jiaying Liu · 2017
Cited alongside, same era.
Online action detection and forecast via multitask deep recurrent neural networks
Chunhui Liu, Yanghao Li, Yueyu Hu, and Jiaying Liu · 2017
Cited alongside, same era.
Thinet: A filter level pruning method for deep neural network compression
Jian-Hao Luo, Jianxin Wu, and Weiyao Lin · 2017
Cited alongside, same era.
Unsupervised video summarization with adversarial lstm networks
Behrooz Mahasseni, Michael Lam, and Sinisa Todorovic · 2017
Cited alongside, same era.
Learning spatio-temporal representation with pseudo-3d residual networks
Zhaofan Qiu, Ting Yao, and Tao Mei · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Eco: Efficient convolutional network for online video understanding
Mohammadreza Zolfaghari, Kamaljeet Singh, and Thomas Brox · 2018
Later among the works it cites.
Slowfast networks for video recognition
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He · 2019
Later among the works it cites.
Large-scale weakly-supervised pre-training for video action recognition
Deepti Ghadiyaram, Du Tran, and Dhruv Mahajan · 2019
Later among the works it cites.
Scsampler: Sampling salient clips from video for efficient action recognition
Bruno Korbar, Du Tran, and Lorenzo Torresani · 2019
Later among the works it cites.
Tsm: Temporal shift module for efficient video understanding
Ji Lin, Chuang Gan, and Song Han · 2019
Later among the works it cites.
Multi-agent reinforcement learning based frame sampling for effective untrimmed video recognition
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Fully convolutional networks for action recognition
Sheng Yu, Yun Cheng, Li Xie, and Shao-Zi Li · 2017
Cited alongside, same era.
Paraphrasing complex network: Network compression via factor transfer
Jangho Kim, SeongUk Park, and Nojun Kwak · 2018
Cited alongside, same era.
A closer look at spatiotemporal convolutions for action recognition
Du Tran, Heng Wang, Lorenzo Torresani, Jamie Ray, Yann LeCun, and Manohar Paluri · 2018
Cited alongside, same era.
Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
Cited alongside, same era.
Rethinking spatiotemporal feature learning: Speed-accuracy trade-offs in video classification
Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy · 2018
Cited alongside, same era.
Wenhao Wu, Dongliang He, Xiao Tan, Shifeng Chen, and Shilei Wen · 2019
Later among the works it cites.
X3d: Expanding architectures for efficient video recognition
Christoph Feichtenhofer · 2020
Later among the works it cites.
Directional temporal modeling for action recognition
Xinyu Li, Bing Shuai, and Joseph Tighe · 2020
Later among the works it cites.
Tea: Temporal excitation and aggregation for action recognition
Yan Li, Bin Ji, Xintian Shi, Jianguo Zhang, Bin Kang, and Limin Wang · 2020
Later among the works it cites.
Temporal pyramid network for action recognition
Ceyuan Yang, Yinghao Xu, Jianping Shi, Bo Dai, and Bolei Zhou · 2020
Later among the works it cites.
Tam: Temporal adaptive module for video recognition
Zhaoyang Liu, Limin Wang, Wayne Wu, Chen Qian, and Tong Lu · 2021
Closest in time.