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Temporal Action Detection (TAD) is an essential and challenging topic in video understanding, aiming to localize the temporal segments containing human action instances and predict the action categories.
THUMOS challenge: Action recognition with a large number of classes
Y.-G. Jiang, J. Liu, A. Roshan Zamir, G. Toderici, I. Laptev, M. Shah, and R. Sukthankar · 2014
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Two-stream convolutional networks for action recognition in videos
Karen Simonyan and Andrew Zisserman · 2014
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Activitynet: A large-scale video benchmark for human activity understanding
Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem, and Juan Carlos Niebles · 2015
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Long-term recurrent convolutional networks for visual recognition and description
Jeffrey Donahue, Lisa Anne Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Kate Saenko, and Trevor Darrell · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Learning spatiotemporal features with 3d convolutional networks
Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri · 2015
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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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Soft-nms–improving object detection with one line of code
Navaneeth Bodla, Bharat Singh, Rama Chellappa, and Larry S Davis · 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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Turn tap: Temporal unit regression network for temporal action proposals
Jiyang Gao, Zhenheng Yang, Kan Chen, Chen Sun, and Ram Nevatia · 2017
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Cascaded boundary regression for temporal action detection
Jiyang Gao, Zhenheng Yang, and Ram Nevatia · 2017
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The kinetics human action video dataset
Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Chloe Hillier, Sudheendra Vijayanarasimhan, Fabio Viola, Tim Green, Trevor Back, Paul Natsev, et al · 2017
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Single shot temporal action detection
Tianwei Lin, Xu Zhao, and Zheng Shou · 2017
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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R-c3d: Region convolutional 3d network for temporal activity detection
Huijuan Xu, Abir Das, and Kate Saenko · 2017
Cited alongside, same era.
Temporal action detection with structured segment networks
Yue Zhao, Yuanjun Xiong, Limin Wang, Zhirong Wu, Xiaoou Tang, and Dahua Lin · 2017
Cited alongside, same era.
Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
Cited alongside, same era.
Rethinking the faster r-cnn architecture for temporal action localization
Yu-Wei Chao, Sudheendra Vijayanarasimhan, Bryan Seybold, David A Ross, Jia Deng, and Rahul Sukthankar · 2018
Cited alongside, same era.
Bsn: Boundary sensitive network for temporal action proposal generation
Tianwei Lin, Xu Zhao, Haisheng Su, Chongjing Wang, and Ming Yang · 2018
Cited alongside, same era.
Fixing weight decay regularization in adam, 2018
Ilya Loshchilov and Frank Hutter · 2018
Accurate temporal action proposal generation with relation-aware pyramid network
Jialin Gao, Zhixiang Shi, Guanshuo Wang, Jiani Li, Yufeng Yuan, Shiming Ge, and Xi Zhou · 2020
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Fast learning of temporal action proposal via dense boundary generator
Chuming Lin, Jian Li, Yabiao Wang, Ying Tai, Donghao Luo, Zhipeng Cui, Chengjie Wang, Jilin Li, Feiyue Huang, and Rongrong Ji · 2020
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Progressive boundary refinement network for temporal action detection
Qinying Liu and Zilei Wang · 2020
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SparseR-CNN: End-to-end object detection with learnable proposals
Peize Sun, Rufeng Zhang, Yi Jiang, Tao Kong, Chenfeng Xu, Wei Zhan, Masayoshi Tomizuka, Lei Li, Zehuan Yuan, Changhu Wang, and Ping Luo · 2020
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G-tad: Sub-graph localization for temporal action detection
Mengmeng Xu, Chen Zhao, David S Rojas, Ali Thabet, and Bernard Ghanem · 2020
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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.
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.
End-to-end, single-stream temporal action detection in untrimmed videos
Shyamal Buch, Victor Escorcia, Bernard Ghanem, Li Fei-Fei, and Juan Carlos Niebles · 2019
Cited alongside, same era.
Slowfast networks for video recognition
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He · 2019
Cited alongside, same era.
Bmn: Boundary-matching network for temporal action proposal generation
Tianwei Lin, Xiao Liu, Xin Li, Errui Ding, and Shilei Wen · 2019
Cited alongside, same era.
Gaussian temporal awareness networks for action localization
Fuchen Long, Ting Yao, Zhaofan Qiu, Xinmei Tian, Jiebo Luo, and Tao Mei · 2019
Cited alongside, same era.
Revisiting anchor mechanisms for temporal action localization
Le Yang, Houwen Peng, Dingwen Zhang, Jianlong Fu, and Junwei Han · 2020
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Bottom-up temporal action localization with mutual regularization
Peisen Zhao, Lingxi Xie, Chen Ju, Ya Zhang, Yanfeng Wang, and Qi Tian · 2020
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Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
Later among the works it cites.
Augmented transformer with adaptive graph for temporal action proposal generation
Shuning Chang, Pichao Wang, Fan Wang, Hao Li, and Jiashi Feng · 2021
Closest in time.
Learning salient boundary feature for anchor-free temporal action localization
Chuming Lin, Chengming Xu, Donghao Luo, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, and Yanwei Fu · 2021
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End-to-end temporal action detection with transformer
Xiaolong Liu, Qimeng Wang, Yao Hu, Xu Tang, Song Bai, and Xiang Bai · 2021
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Temporal context aggregation network for temporal action proposal refinement
Zhiwu Qing, Haisheng Su, Weihao Gan, Dongliang Wang, Wei Wu, Xiang Wang, Yu Qiao, Junjie Yan, Changxin Gao, and Nong Sang · 2021
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Relaxed transformer decoders for direct action proposal generation
Jing Tan, Jiaqi Tang, Limin Wang, and Gangshan Wu · 2021
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Rgb stream is enough for temporal action detection
Chenhao Wang, Hongxiang Cai, Yuxin Zou, and Yichao Xiong · 2021
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Temporal action proposal generation with transformers
Lining Wang, Haosen Yang, Wenhao Wu, Hongxun Yao, and Hujie Huang · 2021
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Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
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