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Action recognition is computationally expensive.
FASTER Recurrent Networks for Video Classification
Zhu, L.; Sevilla-Lara, L.; Tran, D.; Feiszli, M.; Yang, Y.; and Wang, H. 2019 · 1906
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Only Time Can Tell: Discovering Temporal Data for Temporal Modeling
Sevilla-Lara, L.; Zha, S.; Yan, Z.; Goswami, V.; Feiszli, M.; and Torresani, L. 2019 · 1907
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Knowledge Integration Networks for Action Recognition
Zhang, S.; Guo, S.; Wang, L.; Huang, W.; and Scott, M. R. 2020 · 2002
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Imagenet: A large-scale hierarchical image database
Deng, J.; Dong, W.; Socher, R.; Li, L.-J.; Li, K.; and Fei-Fei, L. 2009 · 2009
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UCF101: A dataset of 101 human actions classes from videos in the wild
Soomro, K.; Zamir, A. R.; and Shah, M. 2012 · 2012
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Neural machine translation by jointly learning to align and translate
Bahdanau, D.; Cho, K.; and Bengio, Y. 2014 · 2014
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Large-scale video classification with convolutional neural networks
Karpathy, A.; Toderici, G.; Shetty, S.; Leung, T.; Sukthankar, R.; and Fei-Fei, L. 2014 · 2014
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Glove: Global vectors for word representation
Pennington, J.; Socher, R.; and Manning, C. D. 2014 · 2014
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Two-stream convolutional networks for action recognition in videos
Simonyan, K.; and Zisserman, A. 2014 · 2014
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Activitynet: A large-scale video benchmark for human activity understanding
Caba Heilbron, F.; Escorcia, V.; Ghanem, B.; and Carlos Niebles, J. 2015 · 2015
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Action recognition using visual attention
Sharma, S.; Kiros, R.; and Salakhutdinov, R. 2015 · 2015
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Beyond short snippets: Deep networks for video classification
Yue-Hei Ng, J.; Hausknecht, M.; Vijayanarasimhan, S.; Vinyals, O.; Monga, R.; and Toderici, G. 2015 · 2015
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Youtube-8m: A large-scale video classification benchmark
Abu-El-Haija, S.; Kothari, N.; Lee, J.; Natsev, P.; Toderici, G.; Varadarajan, B.; and Vijayanarasimhan, S. 2016 · 2016
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Long-term recurrent convolutional networks for visual recognition and description
Donahue, J.; Hendricks, L. A.; Rohrbach, M.; Venugopalan, S.; Guadarrama, S.; Saenko, K.; and Darrell, T. 2016 · 2016
Cited alongside, same era.
Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
Cited alongside, same era.
Temporal segment networks: Towards good practices for deep action recognition
Wang, L.; Xiong, Y.; Wang, Z.; Qiao, Y.; Lin, D.; Tang, X.; and Van Gool, L. 2016 · 2016
Cited alongside, same era.
End-to-end learning of action detection from frame glimpses in videos
Yeung, S.; Russakovsky, O.; Mori, G.; and Fei-Fei, L. 2016 · 2016
Cited alongside, same era.
Quo vadis, action recognition? a new model and the kinetics dataset
Carreira, J.; and Zisserman, A. 2017 · 2017
Cited alongside, same era.
Spatiotemporal multiplier networks for video action recognition
What Makes a Video a Video: Analyzing Temporal Information in Video Understanding Models and Datasets
Huang, D.-A.; Ramanathan, V.; Mahajan, D.; Torresani, L.; Paluri, M.; Li, F. F.; and Niebles, J. C. 2018 · 2018
Later among the works it cites.
In the eye of beholder: Joint learning of gaze and actions in first person video
Li, Y.; Liu, M.; and Rehg, J. M. 2018 · 2018
Later among the works it cites.
Mobilenetv2: Inverted residuals and linear bottlenecks
Sandler, M.; Howard, A.; Zhu, M.; Zhmoginov, A.; and Chen, L.-C. 2018 · 2018
Later among the works it cites.
Egocentric activity prediction via event modulated attention
Shen, Y.; Ni, B.; Li, Z.; and Zhuang, N. 2018 · 2018
Later among the works it cites.
Attention is all we need: Nailing down object-centric attention for egocentric activity recognition
Sudhakaran, S.; and Lanz, O. 2018 · 2018
Later among the works it cites.
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Feichtenhofer, C.; Pinz, A.; and Wildes, R. P. 2017 · 2017
Cited alongside, same era.
Attentional pooling for action recognition
Girdhar, R.; and Ramanan, D. 2017 · 2017
Cited alongside, same era.
Human activity recognition using combinatorial Deep Belief Networks
Gowda, S. N. 2017 · 2017
Cited alongside, same era.
The” Something Something” Video Database for Learning and Evaluating Visual Common Sense
Goyal, R.; Kahou, S. E.; Michalski, V.; Materzynska, J.; Westphal, S.; Kim, H.; Haenel, V.; Fruend, I.; Yianilos, P.; Mueller-Freitag, M.; et al. 2017 · 2017
Cited alongside, same era.
Learning latent subevents in activity videos using temporal attention filters
Piergiovanni, A.; Fan, C.; and Ryoo, M. S. 2017 · 2017
Cited alongside, same era.
Inception-v4, inception-resnet and the impact of residual connections on learning
Szegedy, C.; Ioffe, S.; Vanhoucke, V.; and Alemi, A. A. 2017 · 2017
Cited alongside, same era.
Interaction-aware spatio-temporal pyramid attention networks for action classification
Du, Y.; Yuan, C.; Li, B.; Zhao, L.; Li, Y.; and Hu, W. 2018 · 2018
Cited alongside, same era.
Learning to compare: Relation network for few-shot learning
Sung, F.; Yang, Y.; Zhang, L.; Xiang, T.; Torr, P. H.; and Hospedales, T. M. 2018 · 2018
Later among the works it cites.
Non-local neural networks
Wang, X.; Girshick, R.; Gupta, A.; and He, K. 2018 · 2018
Later among the works it cites.
Adding attentiveness to the neurons in recurrent neural networks
Zhang, P.; Xue, J.; Lan, C.; Zeng, W.; Gao, Z.; and Zheng, N. 2018 · 2018
Later among the works it cites.
Attention-Aware Sampling via Deep Reinforcement Learning for Action Recognition
Dong, W.; Zhang, Z.; and Tan, T. 2019 · 2019
Later among the works it cites.
SCSampler: Sampling salient clips from video for efficient action recognition
Korbar, B.; Tran, D.; and Torresani, L. 2019 · 2019
Later among the works it cites.
frame attention networks for facial expression recognition in videos
Meng, D.; Peng, X.; Wang, K.; and Qiao, Y. 2019 · 2019
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Dynamic Motion Representation for Human Action Recognition
Asghari-Esfeden, S.; Sznaier, M.; and Camps, O. 2020 · 2020
Closest in time.
Dynamic Sampling Networks for Efficient Action Recognition in Videos
Zheng, Y.-D.; Liu, Z.; Lu, T.; and Wang, L. 2020 · 2020
Closest in time.