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Existing temporal action localization (TAL) works rely on a large number of training videos with exhaustive segment-level annotation, preventing them from scaling to new classes.
Ucf101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
Earlier work this paper cites.
On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl, and Geoffrey Hinton · 2013
Earlier work this paper cites.
Thumos challenge: Action recognition with a large number of classes, 2014
Yu-Gang Jiang, Jingen Liu, A Roshan Zamir, George Toderici, Ivan Laptev, Mubarak Shah, and Rahul Sukthankar · 2014
Earlier work this paper cites.
Activitynet: A large-scale video benchmark for human activity understanding
Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem, and Juan Carlos Niebles · 2015
Earlier work this paper cites.
Siamese neural networks for one-shot image recognition
Gregory Koch, Richard Zemel, and Ruslan Salakhutdinov · 2015
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Learning spatiotemporal features with 3d convolutional networks
Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri · 2015
Earlier work this paper cites.
Optimization as a model for few-shot learning
Sachin Ravi and Hugo Larochelle · 2016
Earlier work this paper cites.
Temporal action localization in untrimmed videos via multi-stage cnns
Zheng Shou, Dongang Wang, and Shih-Fu Chang · 2016
Earlier work this paper cites.
Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, and Daan Wierstra · 2016
Earlier work this paper cites.
Soft-nms–improving object detection with one line of code
Navaneeth Bodla, Bharat Singh, Rama Chellappa, and Larry S Davis · 2017
Earlier work this paper cites.
Sst: Single-stream temporal action proposals
Shyamal Buch, Victor Escorcia, Chuanqi Shen, Bernard Ghanem, and Juan Carlos Niebles · 2017
Earlier work this paper cites.
Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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Temporal context network for activity localization in videos
Xiyang Dai, Bharat Singh, Guyue Zhang, Larry S Davis, and Yan Qiu Chen · 2017
Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
Cited alongside, same era.
Turn tap: Temporal unit regression network for temporal action proposals
Jiyang Gao, Zhenheng Yang, Kan Chen, Chen Sun, and Ram Nevatia · 2017
Cited alongside, same era.
Low-shot visual recognition by shrinking and hallucinating features
Bharath Hariharan and Ross Girshick · 2017
Cited alongside, same era.
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
Cited alongside, same era.
One-shot learning for semantic segmentation
Amirreza Shaban, Shray Bansal, Zhen Liu, Irfan Essa, and Byron Boots · 2017
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
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Meta-learning with latent embedding optimization
Andrei A Rusu, Dushyant Rao, Jakub Sygnowski, Oriol Vinyals, Razvan Pascanu, Simon Osindero, and Raia Hadsell · 2018
Later among the works it cites.
Learning to compare: Relation network for few-shot learning
Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip HS Torr, and Timothy M Hospedales · 2018
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Low-shot learning from imaginary data
Yu-Xiong Wang, Ross Girshick, Martial Hebert, and Bharath Hariharan · 2018
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One-shot action localization by learning sequence matching network
Hongtao Yang, Xuming He, and Fatih Porikli · 2018
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Jake Snell, Kevin Swersky, and Richard S Zemel · 2017
Cited alongside, same era.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Untrimmednets for weakly supervised action recognition and detection
Limin Wang, Yuanjun Xiong, Dahua Lin, and Luc Van Gool · 2017
Cited alongside, same era.
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.
Few-example object detection with model communication
Xuanyi Dong, Liang Zheng, Fan Ma, Yi Yang, and Deyu Meng · 2018
Cited alongside, same era.
Video re-localization
Yang Feng, Lin Ma, Wei Liu, Tong Zhang, and Jiebo Luo · 2018
Cited alongside, same era.
Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira, Yu-Chiang Frank Wang, and Jia-Bin Huang · 2019
Later among the works it cites.
Silco: Show a few images, localize the common object
Tao Hu, Pascal Mettes, Jia-Hong Huang, and Cees GM Snoek · 2019
Later among the works it cites.
Few-shot object detection via feature reweighting
Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, and Trevor Darrell · 2019
Later among the works it cites.
Graph convolutional networks for temporal action localization
Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, and Chuang Gan · 2019
Later among the works it cites.
Canet: Class-agnostic segmentation networks with iterative refinement and attentive few-shot learning
Chi Zhang, Guosheng Lin, Fayao Liu, Rui Yao, and Chunhua Shen · 2019
Later among the works it cites.
Few-shot semantic segmentation with democratic attention networks
Haochen Wang, Xudong Zhang, Yutao Hu, Yandan Yang, Xianbin Cao, and Xiantong Zhen · 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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Localizing the common action among a few videos
Pengwan Yang, Vincent Tao Hu, Pascal Mettes, and Cees GM Snoek · 2020
Later among the works it cites.