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Temporal relational modeling in video is essential for human action understanding, such as action recognition and action segmentation.
Videograph: Recognizing minutes-long human activities in videos
Hussein, N.; Gavves, E.; and Smeulders, A. W. 2019 · 1905
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A multi-stream bi-directional recurrent neural network for fine-grained action detection
Singh, B.; Marks, T. K.; Jones, M.; Tuzel, O.; and Shao, M. 2016 · 1970
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Action recognition for surveillance applications using optic flow and SVM
Danafar, S.; and Gheissari, N. 2007 · 2007
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The meaning of action: A review on action recognition and mapping
Krüger, V.; Kragic, D.; Ude, A.; and Geib, C. 2007 · 2007
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Understanding egocentric activities
Fathi, A.; Farhadi, A.; and Rehg, J. M. 2011 · 2011
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Learning to recognize objects in egocentric activities
Fathi, A.; Ren, X.; and Rehg, J. M. 2011 · 2011
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A database for fine grained activity detection of cooking activities
Rohrbach, M.; Amin, S.; Andriluka, M.; and Schiele, B. 2012 · 2012
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Modeling actions through state changes
Fathi, A.; and Rehg, J. M. 2013 · 2013
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Combining embedded accelerometers with computer vision for recognizing food preparation activities
Stein, S.; and McKenna, S. J. 2013 · 2013
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Temporal sequence modeling for video event detection
Cheng, Y.; Fan, Q.; Pankanti, S.; and Choudhary, A. 2014 · 2014
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Fast saliency based pooling of fisher encoded dense trajectories
Karaman, S.; Seidenari, L.; and Del Bimbo, A. 2014 · 2014
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The language of actions: Recovering the syntax and semantics of goal-directed human activities
Kuehne, H.; Arslan, A.; and Serre, T. 2014 · 2014
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Parsing videos of actions with segmental grammars
Pirsiavash, H.; and Ramanan, D. 2014 · 2014
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Unsupervised visual representation learning by context prediction
Doersch, C.; Gupta, A.; and Efros, A. A. 2015 · 2015
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Anticipating human activities using object affordances for reactive robotic response
Koppula, H. S.; and Saxena, A. 2015 · 2015
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Connectionist temporal modeling for weakly supervised action labeling
Huang, D.-A.; Fei-Fei, L.; and Niebles, J. C. 2016 · 2016
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An end-to-end generative framework for video segmentation and recognition
Kuehne, H.; Gall, J.; and Serre, T. 2016 · 2016
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Segmental spatiotemporal cnns for fine-grained action segmentation
Lea, C.; Reiter, A.; Vidal, R.; and Hager, G. D. 2016 · 2016
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Learning convolutional action primitives for fine-grained action recognition
Lea, C.; Vidal, R.; and Hager, G. D. 2016 · 2016
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Shuffle and learn: unsupervised learning using temporal order verification
Misra, I.; Zitnick, C. L.; and Hebert, M. 2016 · 2016
Cited alongside, same era.
Planning for autonomous cars that leverage effects on human actions
Sadigh, D.; Sastry, S.; Seshia, S. A.; and Dragan, A. D. 2016 · 2016
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Quo vadis, action recognition? a new model and the kinetics dataset
Carreira, J.; and Zisserman, A. 2017 · 2017
Person re-identification with deep similarity-guided graph neural network
Shen, Y.; Li, H.; Yi, S.; Chen, D.; and Wang, X. 2018 · 2018
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Videos as space-time region graphs
Wang, X.; and Gupta, A. 2018 · 2018
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Spatial temporal graph convolutional networks for skeleton-based action recognition
Yan, S.; Xiong, Y.; and Lin, D. 2018 · 2018
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Graph-based global reasoning networks
Chen, Y.; Rohrbach, M.; Yan, Z.; Shuicheng, Y.; Feng, J.; and Kalantidis, Y. 2019 · 2019
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Ms-tcn: Multi-stage temporal convolutional network for action segmentation
Farha, Y. A.; and Gall, J. 2019 · 2019
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Deep multimodal clustering for unsupervised audiovisual learning
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Cited alongside, same era.
Self-supervised video representation learning with odd-one-out networks
Fernando, B.; Bilen, H.; Gavves, E.; and Gould, S. 2017 · 2017
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Kipf, T. N.; and Welling, M. 2017 · 2017
Cited alongside, same era.
Temporal convolutional networks for action segmentation and detection
Lea, C.; Flynn, M. D.; Vidal, R.; Reiter, A.; and Hager, G. D. 2017 · 2017
Cited alongside, same era.
Unsupervised representation learning by sorting sequences
Lee, H.-Y.; Huang, J.-B.; Singh, M.; and Yang, M.-H. 2017 · 2017
Cited alongside, same era.
Unsupervised representation learning by predicting image rotations
Gidaris, S.; Singh, P.; and Komodakis, N. 2018 · 2018
Cited alongside, same era.
Cooperative learning of audio and video models from self-supervised synchronization
Korbar, B.; Tran, D.; and Torresani, L. 2018 · 2018
Cited alongside, same era.
Hu, D.; Nie, F.; and Li, X. 2019 · 2019
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Autonomous vehicles that interact with pedestrians: A survey of theory and practice
Rasouli, A.; and Tsotsos, J. K. 2019 · 2019
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Graph convolutional networks for temporal action localization
Zeng, R.; Huang, W.; Tan, M.; Rong, Y.; Zhao, P.; Huang, J.; and Gan, C. 2019 · 2019
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A structured model for action detection
Zhang, Y.; Tokmakov, P.; Hebert, M.; and Schmid, C. 2019 · 2019
Later among the works it cites.
Action Segmentation with Mixed Temporal Domain Adaptation
Chen, M.-H.; Li, B.; Bao, Y.; and AlRegib, G. 2020 · 2020
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Discriminative Sounding Objects Localization via Self-supervised Audiovisual Matching
Hu, D.; Qian, R.; Jiang, M.; Tan, X.; Wen, S.; Ding, E.; Lin, W.; and Dou, D. 2020 · 2020
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Improving Action Segmentation via Graph-Based Temporal Reasoning
Huang, Y.; Sugano, Y.; and Sato, Y. 2020 · 2020
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MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation
Li, S.-J.; AbuFarha, Y.; Liu, Y.; Cheng, M.-M.; and Gall, J. 2020 · 2020
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Boundary-Aware Cascade Networks for Temporal Action Segmentation
Wang, Z.; Gao, Z.; Wang, L.; Li, Z.; and Wu, G. 2020 · 2020
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Temporal reasoning graph for activity recognition
Zhang, J.; Shen, F.; Xu, X.; and Shen, H. T. 2020 · 2020
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