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Most approaches for self-supervised learning (SSL) are optimised on curated balanced datasets, e.g.
The pareto, zipf and other power laws
William J Reed · 2001
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Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2003
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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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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Network dissection: Quantifying interpretability of deep visual representations
David Bau, Bolei Zhou, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
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Learning to model the tail
Yu-Xiong Wang, Deva Ramanan, and Martial Hebert · 2017
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Net2vec: Quantifying and explaining how concepts are encoded by filters in deep neural networks
Ruth Fong and Andrea Vedaldi · 2018
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Mining on manifolds: Metric learning without labels
Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, and Ondřej Chum · 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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Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, X Yu Stella, and Dahua Lin · 2018
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Self-labelling via simultaneous clustering and representation learning
Yuki Markus Asano, Christian Rupprecht, and Andrea Vedaldi · 2019
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Class-balanced loss based on effective number of samples
Yin Cui, Menglin Jia, Tsung-Yi Lin, Yang Song, and Serge Belongie · 2019
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Large-scale long-tailed recognition in an open world
Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang, Boqing Gong, and Stella X Yu · 2019
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A theoretical analysis of contrastive unsupervised representation learning
Nikunj Saunshi, Orestis Plevrakis, Sanjeev Arora, Mikhail Khodak, and Hrishikesh Khandeparkar · 2019
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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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Disentangled and controllable face image generation via 3d imitative-contrastive learning
Yu Deng, Jiaolong Yang, Dong Chen, Fang Wen, and Xin Tong · 2020
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Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, et al · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 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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Exploring balanced feature spaces for representation learning
Bingyi Kang, Yu Li, Sa Xie, Zehuan Yuan, and Jiashi Feng · 2020
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Quantifying learnability and describability of visual concepts emerging in representation learning
Iro Laina, Ruth Fong, and Andrea Vedaldi · 2020
Cited alongside, same era.
Contrastive learning with hard negative samples
Joshua Robinson, Ching-Yao Chuang, Suvrit Sra, and Stefanie Jegelka · 2020
Cited alongside, same era.
Self-supervised learning from a multi-view perspective
Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, and Louis-Philippe Morency · 2020
Understanding the behaviour of contrastive loss
Feng Wang and Huaping Liu · 2021
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Solving inefficiency of self-supervised representation learning
Guangrun Wang, Keze Wang, Guangcong Wang, Philip HS Torr, and Liang Lin · 2021
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Toward understanding the feature learning process of self-supervised contrastive learning
Zixin Wen and Yuanzhi Li · 2021
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Decoupled contrastive learning
Chun-Hsiao Yeh, Cheng-Yao Hong, Yen-Chi Hsu, Tyng-Luh Liu, Yubei Chen, and Yann LeCun · 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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Cited alongside, same era.
Understanding contrastive representation learning through alignment and uniformity on the hypersphere
Tongzhou Wang and Phillip Isola · 2020
Cited alongside, same era.
Rethinking the value of labels for improving class-imbalanced learning
Yuzhe Yang and Zhi Xu · 2020
Cited alongside, same era.
Intriguing properties of contrastive losses
Ting Chen, Calvin Luo, and Lala Li · 2021
Cited alongside, same era.
Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 2021
Cited alongside, same era.
Whitening for self-supervised representation learning
Aleksandr Ermolov, Aliaksandr Siarohin, Enver Sangineto, and Nicu Sebe · 2021
Cited alongside, same era.
Obow: Online bag-of-visual-words generation for self-supervised learning
Spyros Gidaris, Andrei Bursuc, Gilles Puy, Nikos Komodakis, Matthieu Cord, and Patrick Perez · 2021
Cited alongside, same era.
Oliver Zhang, Mike Wu, Jasmine Bayrooti, and Noah Goodman · 2021
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Crosspoint: Self-supervised cross-modal contrastive learning for 3d point cloud understanding
Mohamed Afham, Isuru Dissanayake, Dinithi Dissanayake, Amaya Dharmasiri, Kanchana Thilakarathna, and Ranga Rodrigo · 2022
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Vicreg: Variance-invariance-covariance regularization for self-supervised learning
Adrien Bardes, Jean Ponce, and Yann LeCun · 2022
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Beyond supervised vs. unsupervised: Representative benchmarking and analysis of image representation learning
Matthew Gwilliam and Abhinav Shrivastava · 2022
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Dynamic temperature scaling in contrastive self-supervised learning for sensor-based human activity recognition
Bulat Khaertdinov, Stylianos Asteriadis, and Esam Ghaleb · 2022
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Everything at once-multi-modal fusion transformer for video retrieval
Nina Shvetsova, Brian Chen, Andrew Rouditchenko, Samuel Thomas, Brian Kingsbury, Rogerio S Feris, David Harwath, James Glass, and Hilde Kuehne · 2022
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Masked feature prediction for self-supervised visual pre-training
Chen Wei, Haoqi Fan, Saining Xie, Chao-Yuan Wu, Alan Yuille, and Christoph Feichtenhofer · 2022
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Pcl: Proxy-based contrastive learning for domain generalization
Xufeng Yao, Yang Bai, Xinyun Zhang, Yuechen Zhang, Qi Sun, Ran Chen, Ruiyu Li, and Bei Yu · 2022
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Dual temperature helps contrastive learning without many negative samples: Towards understanding and simplifying moco
Chaoning Zhang, Kang Zhang, Trung X Pham, Axi Niu, Zhinan Qiao, Chang D Yoo, and In So Kweon · 2022
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Is self-supervised learning more robust than supervised learning?
Yuanyi Zhong, Haoran Tang, Junkun Chen, Jian Peng, and Yu-Xiong Wang · 2022
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Contrastive learning with boosted memorization
Zhihan Zhou, Jiangchao Yao, Yan-Feng Wang, Bo Han, and Ya Zhang · 2022
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