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Most successful self-supervised learning methods are trained to align the representations of two independent views from the data.
A duality based approach for realtime tv-l 1 optical flow
Christopher Zach, Thomas Pock, and Horst Bischof · 2007
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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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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 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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Discriminative unsupervised feature learning with convolutional neural networks
Alexey Dosovitskiy, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox · 2014
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Two-stream convolutional networks for action recognition in videos
Karen Simonyan and Andrew Zisserman · 2014
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Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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What’s cookin’? Interpreting cooking videos using text, speech and vision
Jonathan Malmaud, Jonathan Huang, Vivek Rathod, Nick Johnston, Andrew Rabinovich, and Kevin Murphy · 2015
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ESC: Dataset for environmental sound classification
Karol J Piczak · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Unsupervised semantic parsing of video collections
Ozan Sener, Amir R. Zamir, Silvio Savarese, and Ashutosh Saxena · 2015
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Unsupervised learning of video representations using lstms
Nitish Srivastava, Elman Mansimov, and Ruslan Salakhudinov · 2015
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Youtube-8m: A large-scale video classification benchmark
Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, and Sudheendra Vijayanarasimhan · 2016
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Unsupervised learning from narrated instruction videos
Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Ivan Laptev, Josef Sivic, and Simon Lacoste-Julien · 2016
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Cliquecnn: Deep unsupervised exemplar learning
Miguel A. Bautista, Artsiom Sanakoyeu, Ekaterina Sutter, and Björn Ommer · 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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Deep multi-scale video prediction beyond mean square error
Michael Mathieu, Camille Couprie, and Yann LeCun · 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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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 Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A. Efros · 2016
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Spatio-temporal video autoencoder with differentiable memory
Viorica Pătrăucean, Ankur Handa, and Roberto Cipolla · 2016
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Generating videos with scene dynamics
Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
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An uncertain future: Forecasting from static images using variational autoencoders
Jacob Walker, Carl Doersch, Abhinav Gupta, and Martial Hebert · 2016
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Unsupervised deep embedding for clustering analysis
Junyuan Xie, Ross Girshick, and Ali Farhadi · 2016
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Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Look, listen and learn
Relja Arandjelović and Andrew Zisserman · 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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Multi-task self-supervised visual learning
Carl Doersch and Andrew Zisserman · 2017
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Vse++: Improving visual-semantic embeddings with hard negatives
Fartash Faghri, David J Fleet, Jamie Ryan Kiros, and Sanja Fidler · 2017
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Audio set: An ontology and human-labeled dataset for audio events
Jort F Gemmeke, Daniel PW Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R Channing Moore, Manoj Plakal, and Marvin Ritter · 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, Mustafa Suleyman, and Andrew Zisserman · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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SGDR: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2017
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Deepcluster: A general clustering framework based on deep learning
Kai Tian, Shuigeng Zhou, and Jihong Guan · 2017
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Self-labelling via simultaneous clustering and representation learning
Yuki Markus Asano, Christian Rupprecht, and Andrea Vedaldi · 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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Representation learning with video deep infomax
R Devon et al · 2020
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Learning representations by predicting bags of visual words
Spyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, and Matthieu Cord · 2020
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Objects that sound
Relja Arandjelović and Andrew Zisserman · 2018
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Deep clustering for unsupervised learning of visual features
Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze · 2018
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A short note about kinetics-600
Joao Carreira, Eric Noland, Andras Banki-Horvath, Chloe Hillier, and Andrew Zisserman · 2018
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Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
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Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, and Yoshua Bengio · 2018
Cited alongside, same era.
Unsupervised learning of semantic audio representations
Aren Jansen, Manoj Plakal, Ratheet Pandya, Daniel PW Ellis, Shawn Hershey, Jiayang Liu, R Channing Moore, and Rif A Saurous · 2018
Cited alongside, same era.
Cooperative learning of audio and video models from self-supervised synchronization
Bruno Korbar, Du Tran, and Lorenzo Torresani · 2018
Cited alongside, same era.
Shreyank N Gowda, Marcus Rohrbach, and Laura Sevilla-Lara · 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 H Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, et al · 2020
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Bootstrap latent-predictive representations for multitask reinforcement learning
Zhaohan Daniel Guo, Bernardo Avila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Rémi Munos, and Mohammad Gheshlaghi Azar · 2020
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Memory-augmented dense predictive coding for video representation learning
Tengda Han, Weidi Xie, and Andrew Zisserman · 2020
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Self-supervised co-training for video representation learning
Tengda Han, Weidi Xie, and Andrew Zisserman · 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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Data-efficient image recognition with contrastive predictive coding
Olivier J Hénaff, Ali Razavi, Carl Doersch, SM Eslami, and Aaron van den Oord · 2020
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Improved baselines with momentum contrastive learning
Rishabh Jain, Haoqi Fan, Ross B. Girshick, and Kaiming He · 2020
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Coincidence, categorization, and consolidation: Learning to recognize sounds with minimal supervision
Aren Jansen, Daniel PW Ellis, Shawn Hershey, R Channing Moore, Manoj Plakal, Ashok C Popat, and Rif A Saurous · 2020
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Panns: Large-scale pretrained audio neural networks for audio pattern recognition
Qiuqiang Kong, Yin Cao, Turab Iqbal, Yuxuan Wang, Wenwu Wang, and Mark D Plumbley · 2020
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Contrastive representation learning: A framework and review
Phuc H Le-Khac, Graham Healy, and Alan F Smeaton · 2020
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Network randomization: A simple technique for generalization in deep reinforcement learning
Kimin Lee, Kibok Lee, Jinwoo Shin, and Honglak Lee · 2020
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End-to-End Learning of Visual Representations from Uncurated Instructional Videos
Antoine Miech, Jean-Baptiste Alayrac, Lucas Smaira, Ivan Laptev, Josef Sivic, and Andrew Zisserman · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Audio-visual instance discrimination with cross-modal agreement
Pedro Morgado, Nuno Vasconcelos, and Ishan Misra · 2020
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Multi-modal self-supervision from generalized data transformations
Mandela Patrick, Yuki M. Asano, Ruth Fong, João F. Henriques, Geoffrey Zweig, and Andrea Vedaldi · 2020
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Evolving losses for unsupervised video representation learning
AJ Piergiovanni, Anelia Angelova, and Michael S Ryoo · 2020
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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 · 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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Visual grounding in video for unsupervised word translation
Gunnar A Sigurdsson, Jean-Baptiste Alayrac, Aida Nematzadeh, Lucas Smaira, Mateusz Malinowski, João Carreira, Phil Blunsom, and Andrew Zisserman · 2020
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D3d: Distilled 3d networks for video action recognition
Jonathan Stroud, David Ross, Chen Sun, Jia Deng, and Rahul Sukthankar · 2020
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What makes for good views for contrastive learning
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, and Phillip Isola · 2020
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Robust and generalizable visual representation learning via random convolutions
Zhenlin Xu, Deyi Liu, Junlin Yang, and Marc Niethammer · 2020
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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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A large-scale study on unsupervised spatiotemporal representation learning
Christoph Feichtenhofer, Haoqi Fan, Bo Xiong, Ross Girshick, and Kaiming He · 2021
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Ast: Audio spectrogram transformer
Yuan Gong, Yu-An Chung, and James Glass · 2021
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