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We propose SCVRL, a novel contrastive-based framework for self-supervised learning for videos.
Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun · 2006
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Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol · 2008
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HMDB: a large video database for human motion recognition
Hildegard Kuehne, Hueihan Jhuang, Estibaliz Garrote, Tomaso Poggio, and Thomas Serre · 2011
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A dataset of 101 human action classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and M Shah · 2013
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History and definition of the sobel operator
Irwin Sobel · 2014
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Unsupervised Learning of Visual Representations using Videos
Xiaolong Wang and Abhinav Gupta · 2015
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Shuffle and learn: unsupervised learning using temporal order verification
Ishan Misra, C Lawrence Zitnick, and Martial Hebert · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krähenbühl, Jeff Donahue, Trevor Darrell, and Alexei A. Efros · 2016
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LSTM self-supervision for detailed behavior analysis
Biagio Brattoli, Uta Buchler, Anna-Sophia Wahl, Martin E Schwab, and Bjorn Ommer · 2017
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The ”something something” video database for learning and evaluating visual common sense
Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fründ, Peter Yianilos, Moritz Mueller-Freitag, Florian Hoppe, Christian Thurau, Ingo Bax, and Roland Memisevic · 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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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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Unsupervised representation learning by sorting sequences
Hsin-Ying Lee, Jia-Bin Huang, Maneesh Singh, and Ming-Hsuan Yang · 2017
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Unsupervised representation learning by sorting sequences
Hsin-Ying Lee, Jia-Bin Huang, Maneesh Singh, and Ming-Hsuan Yang · 2017
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Representation learning by learning to count
Mehdi Noroozi, Hamed Pirsiavash, and Paolo Favaro · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Improving spatiotemporal self-supervision by deep reinforcement learning
Uta Buchler, Biagio Brattoli, and Bjorn Ommer · 2018
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Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
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RESOUND: towards action recognition without representation bias
Yingwei Li, Yi Li, and Nuno Vasconcelos · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Self-supervised video hashing with hierarchical binary auto-encoder
Jingkuan Song, Hanwang Zhang, Xiangpeng Li, Lianli Gao, Meng Wang, and Richang Hong · 2018
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Tracking emerges by colorizing videos
Carl Vondrick, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama, and Kevin Murphy · 2018
Cited alongside, same era.
Learning and using the arrow of time
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Diva: Diverse visual feature aggregation for deep metric learning
Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, and Joseph Paul Cohen · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Vivit: A video vision transformer
Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lucic, and Cordelia Schmid · 2021
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Is space-time attention all you need for video understanding?
Gedas Bertasius, Heng Wang, and Lorenzo Torresani · 2021
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Behavior-driven synthesis of human dynamics
Andreas Blattmann, Timo Milbich, Michael Dorkenwald, and Bjorn Ommer · 2021
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Donglai Wei, Joseph J Lim, Andrew Zisserman, and William T Freeman · 2018
Cited alongside, same era.
Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X Yu, and Dahua Lin · 2018
Cited alongside, same era.
Learning representations by maximizing mutual information across views
Philip Bachman, R. Devon Hjelm, and William Buchwalter · 2019
Cited alongside, same era.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
DynamoNet: Dynamic action and motion network
Ali Diba, Vivek Sharma, Luc Van Gool, and Rainer Stiefelhagen · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Learning correspondence from the cycle-consistency of time
Xiaolong Wang, Allan Jabri, and Alexei A Efros · 2019
Cited alongside, same era.
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ipoke: Poking a still image for controlled stochastic video synthesis
Andreas Blattmann, Timo Milbich, Michael Dorkenwald, and Björn Ommer · 2021
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Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 2021
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Stochastic image-to-video synthesis using cinns
Michael Dorkenwald, Timo Milbich, Andreas Blattmann, Robin Rombach, Konstantinos G. Derpanis, and Bjorn Ommer · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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Contrast and order representations for video self-supervised learning
Kai Hu, Jie Shao, Yuan Liu, Bhiksha Raj, Marios Savvides, and Zhiqiang Shen · 2021
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Spatiotemporal contrastive video representation learning
Rui Qian, Tianjian Meng, Boqing Gong, Ming-Hsuan Yang, Huisheng Wang, Serge Belongie, and Yin Cui · 2021
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Do vision transformers see like convolutional neural networks?
Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, and Alexey Dosovitskiy · 2021
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Only time can tell: Discovering temporal data for temporal modeling
Laura Sevilla-Lara, Shengxin Zha, Zhicheng Yan, Vedanuj Goswami, Matt Feiszli, and Lorenzo Torresani · 2021
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Modist: Motion distillation for self-supervised video representation learning
Fanyi Xiao, Joseph Tighe, and Davide Modolo · 2021
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Multi-scale vision longformer: A new vision transformer for high-resolution image encoding
Pengchuan Zhang, Xiyang Dai, Jianwei Yang, Bin Xiao, Lu Yuan, Lei Zhang, and Jianfeng Gao · 2021
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Tuber: Tube-transformer for action detection
Jiaojiao Zhao, Xinyu Li, Chunhui Liu, Bing Shuai, Hao Chen, Cees G. M. Snoek, and Joseph Tighe · 2021
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Sharing matters for generalization in deep metric learning
Timo Milbich, Karsten Roth, Biagio Brattoli, and Björn Ommer · 2022
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