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Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
M. Gutmann and A. Hyvärinen · 2010
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Hmdb: a large video database for human motion recognition
Hildegard Kuehne, Hueihan Jhuang, Estíbaliz Garrote, Tomaso Poggio, and Thomas Serre · 2011
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Hard negative mixing for contrastive learning
Yannis Kalantidis, Mert Bulent Sariyildiz, Noe Pion, Philippe Weinzaepfel, and Diane Larlus · 2011
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Ucf101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
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Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics
Michael U. Gutmann and Aapo Hyvärinen · 2012
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Efficient estimation of word representations in vector space, 2013
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Distributed representations of words and phrases and their compositionality, 2013
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Generative adversarial networks, 2014
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Discriminative unsupervised feature learning with exemplar convolutional neural networks, 2014
Alexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox · 2014
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Describing textures in the wild
Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Sammy Mohamed, and Andrea Vedaldi · 2014
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Adam: A method for stochastic optimization, 2014
Diederik P. Kingma and Jimmy Ba · 2014
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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Russ R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler · 2015
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Pixel recurrent neural networks, 2016
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Generative adversarial text to image synthesis, 2016
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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The empty brain, 2016
Robert Epstein · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Sgdr: Stochastic gradient descent with warm restarts, 2016
Ilya Loshchilov and Frank Hutter · 2016
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Unsupervised visual representation learning by context prediction, 2016
Carl Doersch, Abhinav Gupta, and Alexei A. Efros · 2016
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Context encoders: Feature learning by inpainting, 2016
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A. Efros · 2016
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Colorful image colorization, 2016
Richard Zhang, Phillip Isola, and Alexei A. Efros · 2016
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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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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Learning to discover cross-domain relations with generative adversarial networks, 2017
Taeksoo Kim, Moonsu Cha, Hyunsoo Kim, Jung Kwon Lee, and Jiwon Kim · 2017
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Unsupervised learning by predicting noise, 2017
Piotr Bojanowski and Armand Joulin · 2017
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Time-contrastive networks: Self-supervised learning from video, 2017
Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, and Sergey Levine · 2017
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Tobias Glasmachers · 2017
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Accurate, large minibatch sgd: Training imagenet in 1 hour, 2017
Priya Goyal, Piotr Dollár, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He · 2017
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Large batch training of convolutional networks, 2017
Yang You, Igor Gitman, and Boris Ginsburg · 2017
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Places: A 10 million image database for scene recognition, 2017
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 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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Adversarial feature learning, 2017
Jeff Donahue, Philipp Krähenbühl, and Trevor Darrell · 2017
Cited alongside, same era.
Split-brain autoencoders: Unsupervised learning by cross-channel prediction, 2017
Richard Zhang, Phillip Isola, and Alexei A. Efros · 2017
Cited alongside, same era.
Unsupervised representation learning by sorting sequences
Hsin-Ying Lee, Jia-Bin Huang, Maneesh Singh, and Ming-Hsuan Yang · 2017
Aet vs. aed: Unsupervised representation learning by auto-encoding transformations rather than data, 2019
Liheng Zhang, Guo-Jun Qi, Liqiang Wang, and Jiebo Luo · 2019
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Scaling and benchmarking self-supervised visual representation learning, 2019
Priya Goyal, Dhruv Mahajan, Abhinav Gupta, and Ishan Misra · 2019
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Self-supervised video representation learning with space-time cubic puzzles
Dahun Kim, Donghyeon Cho, and In So Kweon · 2019
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Contrastive multiview coding, 2019
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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A theoretical analysis of contrastive unsupervised representation learning, 2019
Sanjeev Arora, Hrishikesh Khandeparkar, Mikhail Khodak, Orestis Plevrakis, and Nikunj Saunshi · 2019
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Cross-lingual language model pretraining, 2019
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Cited alongside, same era.
Self-supervised video representation learning with odd-one-out networks
Basura Fernando, Hakan Bilen, Efstratios Gavves, and Stephen Gould · 2017
Cited alongside, same era.
Unsupervised feature learning via non-parametric instance-level discrimination, 2018
Zhirong Wu, Yuanjun Xiong, Stella Yu, and Dahua Lin · 2018
Cited alongside, same era.
Representation learning with contrastive predictive coding, 2018
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding, 2018
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
Improving language understanding by generative pre-training, 2018
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
Cited alongside, same era.
Learning deep representations by mutual information estimation and maximization, 2018
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, and Yoshua Bengio · 2018
Cited alongside, same era.
Guillaume Lample and Alexis Conneau · 2019
Later among the works it cites.
Self-supervised learning: Generative or contrastive, 2020
Xiao Liu, Fanjin Zhang, Zhenyu Hou, Zhaoyu Wang, Li Mian, Jing Zhang, and Jie Tang · 2020
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Unsupervised learning of visual features by contrasting cluster assignments, 2020
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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A simple framework for contrastive learning of visual representations, 2020
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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What makes for good views for contrastive learning, 2020
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, and Phillip Isola · 2020
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Spatiotemporal contrastive video representation learning, 2020
Rui Qian, Tianjian Meng, Boqing Gong, Ming-Hsuan Yang, Huisheng Wang, Serge Belongie, and Yin Cui · 2020
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Temporal contrastive pretraining for video action recognition
Guillaume Lorre, Jaonary Rabarisoa, Astrid Orcesi, Samia Ainouz, and Stephane Canu · 2020
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Self-supervised video representation learning using inter-intra contrastive framework, 2020
Li Tao, Xueting Wang, and Toshihiko Yamasaki · 2020
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What should not be contrastive in contrastive learning, 2020
Tete Xiao, Xiaolong Wang, Alexei A. Efros, and Trevor Darrell · 2020
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Supervised contrastive learning, 2020
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan · 2020
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Curl: Contrastive unsupervised representations for reinforcement learning, 2020
Aravind Srinivas, Michael Laskin, and Pieter Abbeel · 2020
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Graphcl: Contrastive self-supervised learning of graph representations, 2020
Hakim Hafidi, Mounir Ghogho, Philippe Ciblat, and Ananthram Swami · 2020
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Improved baselines with momentum contrastive learning, 2020
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2020
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Prototypical contrastive learning of unsupervised representations, 2020
Junnan Li, Pan Zhou, Caiming Xiong, Richard Socher, and Steven C. H. Hoi · 2020
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Hand-reha: dynamic hand gesture recognition for game-based wrist rehabilitation
Farnaz Farahanipad, Harish Ram Nambiappan, Ashish Jaiswal, Maria Kyrarini, and Fillia Makedon · 2020
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Self-supervised video representation learning using inter-intra contrastive framework, 2020
Li Tao, Xueting Wang, and Toshihiko Yamasaki · 2020
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Seco: Exploring sequence supervision for unsupervised representation learning, 2020
Ting Yao, Yiheng Zhang, Zhaofan Qiu, Yingwei Pan, and Tao Mei · 2020
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Dtg-net: Differentiated teachers guided self-supervised video action recognition, 2020
Ziming Liu, Guangyu Gao, AK Qin, and Jinyang Li · 2020
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Pretraining with contrastive sentence objectives improves discourse performance of language models, 2020
Dan Iter, Kelvin Guu, Larry Lansing, and Dan Jurafsky · 2020
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Infoxlm: An information-theoretic framework for cross-lingual language model pre-training, 2020
Zewen Chi, Li Dong, Furu Wei, Nan Yang, Saksham Singhal, Wenhui Wang, Xia Song, Xian-Ling Mao, Heyan Huang, and Ming Zhou · 2020
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Cert: Contrastive self-supervised learning for language understanding, 2020
Hongchao Fang, Sicheng Wang, Meng Zhou, Jiayuan Ding, and Pengtao Xie · 2020
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Declutr: Deep contrastive learning for unsupervised textual representations, 2020
John M. Giorgi, Osvald Nitski, Gary D. Bader, and Bo Wang · 2020
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Demystifying contrastive self-supervised learning: Invariances, augmentations and dataset biases, 2020
Senthil Purushwalkam and Abhinav Gupta · 2020
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Self-supervised learning from a multi-view perspective, 2020
Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, and Louis-Philippe Morency · 2020
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