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Self-supervised learning has shown its great potential to extract powerful visual representations without human annotations.
Learning a similarity metric discriminatively, with application to face verification
Sumit Chopra, Raia Hadsell, and Yann LeCun · 2005
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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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Distance metric learning for large margin nearest neighbor classification
Kilian Q Weinberger and Lawrence K Saul · 2009
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Accurate, large minibatch sgd: Training imagenet in 1 hour
Priya Goyal, Piotr Dollár, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He · 2017
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Scaling sgd batch size to 32k for imagenet training
Yang You, Igor Gitman, and Boris Ginsburg · 2017
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2018
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Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
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Parametric instance classification for unsupervised visual feature learning
Yue Cao, Zhenda Xie, Bin Liu, Yutong Lin, Zheng Zhang, and Han Hu · 2020
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Unsupervised learning of visual features by contrasting cluster assignments
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
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2020
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Imagenet terms of access
ImageNet contributors · 2020
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Flickr terms & conditions of use
Inc. Flickr · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 2021
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An empirical study of training self-supervised vision transformers
Xinlei Chen, Saining Xie, and Kaiming He · 2021
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Whitening for self-supervised representation learning
Aleksandr Ermolov, Aliaksandr Siarohin, Enver Sangineto, and Nicu Sebe · 2021
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Adco: Adversarial contrast for efficient learning of unsupervised representations from self-trained negative adversaries
Qianjiang Hu, Xiao Wang, Wei Hu, and Guo-Jun Qi · 2021
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On feature decorrelation in self-supervised learning
Tianyu Hua, Wenxiao Wang, Zihui Xue, Yue Wang, Sucheng Ren, and Hang Zhao · 2021
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Prototypical contrastive learning of unsupervised representations
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Bootstrap your own latent - a new approach to self-supervised learning
Grill Jean-Bastien, Strub Florian, Altché Florent, Tallec Corentin, Pierre Richemond H., Buchatskaya Elena, Doersch Carl, Bernardo Pires Avila, Zhaohan Guo Daniel, Mohammad Azar Gheshlaghi, Piot Bilal, Kavukcuoglu Koray, Munos Rémi, and Valko Michal · 2020
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Hard negative mixing for contrastive learning
Yannis Kalantidis, Mert Bulent Sariyildiz, Noe Pion, Philippe Weinzaepfel, and Diane Larlus · 2020
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Byol works even without batch statistics
Pierre H Richemond, Jean-Bastien Grill, Florent Altché, Corentin Tallec, Florian Strub, Andrew Brock, Samuel Smith, Soham De, Razvan Pascanu, Bilal Piot, et al · 2020
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Understanding contrastive representation learning through alignment and uniformity on the hypersphere
Tongzhou Wang and Phillip Isola · 2020
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Vicreg: Variance-invariance-covariance regularization for self-supervised learning
Adrien Bardes, Jean Ponce, and Yann LeCun · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Junnan Li, Pan Zhou, Caiming Xiong, and Steven CH Hoi · 2021
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Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Bin Liu, and Nenghai Yu · 2021
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Understanding self-supervised learning dynamics without contrastive pairs
Yuandong Tian, Xinlei Chen, and Surya Ganguli · 2021
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Self-supervised learning by estimating twin class distributions
Feng Wang, Tao Kong, Rufeng Zhang, Huaping Liu, and Hang Li · 2021
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Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
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Improving contrastive learning by visualizing feature transformation
Rui Zhu, Bingchen Zhao, Jingen Liu, Zhenglong Sun, and Chang Wen Chen · 2021
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