A curated list of awesome Self-Supervised Learning resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awesome-deep-learning-papers, and awesome-architecture-search
Self-Supervised Learning has become an exciting direction in AI community.
- Jitendra Malik: "Supervision is the opium of the AI researcher"
- Alyosha Efros: "The AI revolution will not be supervised"
- Yann LeCun: "self-supervised learning is the cake, supervised learning is the icing on the cake, reinforcement learning is the cherry on the cake"
Please help contribute this list by pull request
Markdown format:
- Paper Name.
[[pdf]](link)
[[code]](link)
- Author 1, Author 2, and Author 3. *Conference Year*- Theory
- Computer Vision (CV)
- Machine Learning
- Robotics
- Natural Language Processing (NLP)
- Automatic Speech Recognition (ASR)
- Time-Series
- Graph
- Talks
- Thesis
- Blog
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A Theoretical Analysis of Contrastive Unsupervised Representation Learning. [pdf]
- Sanjeev Arora, Hrishikesh Khandeparkar, Mikhail Khodak, Orestis Plevrakis, and Nikunj Saunshi. ICML 2019
-
Towards the Generalization of Contrastive Self-Supervised Learning. [pdf]
- Weiran Huang, Mingyang Yi, and Xuyang Zhao.
-
Understanding the Behaviour of Contrastive Loss. [pdf]
- Feng Wang and Huaping Liu. CVPR 2021
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Predicting What You Already Know Helps: Provable Self-Supervised Learning. [pdf]
- Jason D. Lee, Qi Lei, Nikunj Saunshi, and Jiacheng Zhuo.
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Contrastive learning , multi-view redundancy , and linear models. [pdf]
- Christopher Tosh, Akshay Krishnamurthy, and Daniel Hsu.
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Understanding Self-supervised Learning with Dual Deep Networks. [pdf]
- Yuandong Tian, Lantao Yu, Xinlei Chen, and Surya Ganguli.
-
For self-supervised learning, Rationality implies generalization, provably. [pdf]
- Yamini Bansal, Gal Kaplun, and Boaz Barak.
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Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis. [pdf]
- Jiaye Teng, Weiran Huang, and Haowei He. AISTATS 2022
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Contrastive Representation Learning: A Framework and Review [pdf]
- Phuc H. Le-Khac, Graham Healy, Alan F. Smeaton. IEEE Access 2020
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A Survey on Contrastive Self-supervised Learning [pdf]
- Ashish Jaiswal, Ashwin R Babu, Mohammad Z Zadeh, Debapriya Banerjee, Fillia Makedon
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Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey. [pdf]
- Longlong Jing and Yingli Tian. T-PAMI 2020
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Self-supervised Learning: Generative or Contrastive [pdf]
- Xiao Liu, Fanjin Zhang, Zhenyu Hou, Li Mian, Zhaoyu Wang, Jing Zhang, Jie Tang. TKDE 2021
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Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training [pdf]
- Utku Ozbulak, Hyun Jung Lee, Beril Boga, Esla Timothy Anzaku, Ho-min Park, Arnout Van Messem, Wesley De Neve, Joris Vankerschaver. TMLR 2023
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FAIR Self-Supervision Benchmark [pdf] [repo]: various benchmark (and legacy) tasks for evaluating quality of visual representations learned by various self-supervision approaches.
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How Well Do Self-Supervised Models Transfer? [pdf] [repo]: A benchmark for evaluating self-supervision consisting of many-shot/few-shot recognition, object detection, surface normal estimation and semantic segmentation.
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Unsupervised Visual Representation Learning by Context Prediction. [pdf] [code]
- Doersch, Carl and Gupta, Abhinav and Efros, Alexei A. ICCV 2015
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Unsupervised Learning of Visual Representations using Videos. [pdf] [code]
- Wang, Xiaolong and Gupta, Abhinav. ICCV 2015
-
Learning to See by Moving. [pdf] [code]
- Agrawal, Pulkit and Carreira, Joao and Malik, Jitendra. ICCV 2015
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Learning image representations tied to ego-motion. [pdf] [code]
- Jayaraman, Dinesh and Grauman, Kristen. ICCV 2015
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Joint Unsupervised Learning of Deep Representations and Image Clusters. [pdf] [code-torch] [code-caffe]
- Jianwei Yang, Devi Parikh, Dhruv Batra. CVPR 2016
-
Unsupervised Deep Embedding for Clustering Analysis. [pdf] [code]
- Junyuan Xie, Ross Girshick, and Ali Farhadi. ICML 2016
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Slow and steady feature analysis: higher order temporal coherence in video. [pdf]
- Jayaraman, Dinesh and Grauman, Kristen. CVPR 2016
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Context Encoders: Feature Learning by Inpainting. [pdf] [code]
- Pathak, Deepak and Krahenbuhl, Philipp and Donahue, Jeff and Darrell, Trevor and Efros, Alexei A. CVPR 2016
-
Colorful Image Colorization. [pdf] [code]
- Zhang, Richard and Isola, Phillip and Efros, Alexei A. ECCV 2016
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Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles. [pdf] [code]
- Noroozi, Mehdi and Favaro, Paolo. ECCV 2016
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Ambient Sound Provides Supervision for Visual Learning. [pdf] [code]
- Owens, Andrew and Wu, Jiajun and McDermott, Josh and Freeman, William and Torralba, Antonio. ECCV 2016
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Learning Representations for Automatic Colorization. [pdf] [code]
- Larsson, Gustav and Maire, Michael and Shakhnarovich, Gregory. ECCV 2016
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Unsupervised Visual Representation Learning by Graph-based Consistent Constraints. [pdf] [code]
- Li, Dong and Hung, Wei-Chih and Huang, Jia-Bin and Wang, Shengjin and Ahuja, Narendra and Yang, Ming-Hsuan. ECCV 2016
-
Adversarial Feature Learning. [pdf] [code]
- Donahue, Jeff and Krahenbuhl, Philipp and Darrell, Trevor. ICLR 2017
-
Self-supervised learning of visual features through embedding images into text topic spaces. [pdf] [code]
- L. Gomez* and Y. Patel* and M. Rusiñol and D. Karatzas and C.V. Jawahar. CVPR 2017
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Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. [pdf] [code]
- Zhang, Richard and Isola, Phillip and Efros, Alexei A. CVPR 2017
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Learning Features by Watching Objects Move. [pdf] [code]
- Pathak, Deepak and Girshick, Ross and Dollar, Piotr and Darrell, Trevor and Hariharan, Bharath. CVPR 2017
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Colorization as a Proxy Task for Visual Understanding. [pdf] [code]
- Larsson, Gustav and Maire, Michael and Shakhnarovich, Gregory. CVPR 2017
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DeepPermNet: Visual Permutation Learning. [pdf] [code]
- Cruz, Rodrigo Santa and Fernando, Basura and Cherian, Anoop and Gould, Stephen. CVPR 2017
-
Unsupervised Learning by Predicting Noise. [pdf] [code]
- Bojanowski, Piotr and Joulin, Armand. ICML 2017
-
Multi-task Self-Supervised Visual Learning. [pdf]
- Doersch, Carl and Zisserman, Andrew. ICCV 2017
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Representation Learning by Learning to Count. [pdf]
- Noroozi, Mehdi and Pirsiavash, Hamed and Favaro, Paolo. ICCV 2017
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Transitive Invariance for Self-supervised Visual Representation Learning. [pdf]
- Wang, Xiaolong and He, Kaiming and Gupta, Abhinav. ICCV 2017
-
Look, Listen and Learn. [pdf]
- Relja, Arandjelovic and Zisserman, Andrew. ICCV 2017
-
Unsupervised Representation Learning by Sorting Sequences. [pdf] [code]
- Hsin-Ying Lee, Jia-Bin Huang, Maneesh Kumar Singh, and Ming-Hsuan Yang. ICCV 2017
-
Unsupervised Feature Learning via Non-parameteric Instance Discrimination [pdf] [code]
- Zhirong Wu, Yuanjun Xiong and X Yu Stella and Dahua Lin. CVPR 2018
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Learning Image Representations by Completing Damaged Jigsaw Puzzles. [pdf] [code]
- Kim, Dahun and Cho, Donghyeon and Yoo, Donggeun and Kweon, In So. WACV 2018
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Unsupervised Representation Learning by Predicting Image Rotations. [pdf] [code]
- Spyros Gidaris and Praveer Singh and Nikos Komodakis. ICLR 2018
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Learning Latent Representations in Neural Networks for Clustering through Pseudo Supervision and Graph-based Activity Regularization. [pdf] [code]
- Ozsel Kilinc and Ismail Uysal. ICLR 2018
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Improvements to context based self-supervised learning. [pdf]
- Terrell Mundhenk and Daniel Ho and Barry Chen. CVPR 2018
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Self-Supervised Feature Learning by Learning to Spot Artifacts. [pdf] [code]
- Simon Jenni and Universität Bern and Paolo Favaro. CVPR 2018
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Boosting Self-Supervised Learning via Knowledge Transfer. [pdf]
- Mehdi Noroozi and Ananth Vinjimoor and Paolo Favaro and Hamed Pirsiavash. CVPR 2018
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Cross-domain Self-supervised Multi-task Feature Learning Using Synthetic Imagery. [pdf] [code]
- Zhongzheng Ren and Yong Jae Lee. CVPR 2018
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ShapeCodes: Self-Supervised Feature Learning by Lifting Views to Viewgrids. [pdf]
- Dinesh Jayaraman*, UC Berkeley; Ruohan Gao, University of Texas at Austin; Kristen Grauman. ECCV 2018
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Deep Clustering for Unsupervised Learning of Visual Features [pdf] [code]
- Mathilde Caron, Piotr Bojanowski, Armand Joulin, Matthijs Douze. ECCV 2018
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Cross Pixel Optical-Flow Similarity for Self-Supervised Learning. [pdf]
- Aravindh Mahendran, James Thewlis, Andrea Vedaldi. ACCV 2018
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Representation Learning with Contrastive Predictive Coding. [pdf]
- Aaron van den Oord, Yazhe Li, Oriol Vinyals.
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Self-Supervised Learning via Conditional Motion Propagation. [pdf] [code]
- Xiaohang Zhan, Xingang Pan, Ziwei Liu, Dahua Lin, and Chen Change Loy. CVPR 2019
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Self-Supervised Representation Learning by Rotation Feature Decoupling. [pdf] [code]
- Zeyu Feng; Chang Xu; Dacheng Tao. CVPR 2019
-
Revisiting Self-Supervised Visual Representation Learning. [pdf] [code]
- Alexander Kolesnikov; Xiaohua Zhai; Lucas Beye. CVPR 2019
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Self-Supervised GANs via Auxiliary Rotation Loss. [pdf] [code]
- Ting Chen; Xiaohua Zhai; Marvin Ritter; Mario Lucic; Neil Houlsby. CVPR 2019
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AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data. [pdf] [code]
- Liheng Zhang, Guo-Jun Qi, Liqiang Wang, Jiebo Luo. CVPR 2019
-
Unsupervised Deep Learning by Neighbourhood Discovery. [pdf]. [code].
- Jiabo Huang, Qi Dong, Shaogang Gong, Xiatian Zhu. ICML 2019
-
Contrastive Multiview Coding. [pdf] [code]
- Yonglong Tian and Dilip Krishnan and Phillip Isola.
-
Large Scale Adversarial Representation Learning. [pdf]
- Jeff Donahue, Karen Simonyan.
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Learning Representations by Maximizing Mutual Information Across Views. [pdf] [code]
- Philip Bachman, R Devon Hjelm, William Buchwalter
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Selfie: Self-supervised Pretraining for Image Embedding. [pdf]
- Trieu H. Trinh, Minh-Thang Luong, Quoc V. Le
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Data-Efficient Image Recognition with Contrastive Predictive Coding [pdf]
- Olivier J. He ́naff, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aaron van den Oord
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Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty [pdf] [code]
- Dan Hendrycks, Mantas Mazeika, Saurav Kadavath, Dawn Song. NeurIPS 2019
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Boosting Few-Shot Visual Learning with Self-Supervision [pdf]
- Pyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, and Matthieu Cord. ICCV 2019
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Self-Supervised Generalisation with Meta Auxiliary Learning [pdf] [code]
- Shikun Liu, Andrew J. Davison, Edward Johns. NeurIPS 2019
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Wasserstein Dependency Measure for Representation Learning [pdf] [code]
- Sherjil Ozair, Corey Lynch, Yoshua Bengio, Aaron van den Oord, Sergey Levine, Pierre Sermanet. NeurIPS 2019
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Scaling and Benchmarking Self-Supervised Visual Representation Learning [pdf] [code]
- Priya Goyal, Dhruv Mahajan, Abhinav Gupta, Ishan Misra. ICCV 2019
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Unsupervised Pre-Training of Image Features on Non-Curated Data [pdf] [code]
- Mathilde Caron, Piotr Bojanowski, Julien Mairal, Armand Joulin. ICCV 2019 Oral
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S4L: Self-Supervised Semi-Supervised Learning [pdf] [code]
- Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, Lucas Beyer. ICCV 2019
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Self-supervised model adaptation for multimodal semantic segmentation. [pdf] [code]
- Abhinav Valada, Rohit Mohan, and Wolfram Burgard. IJCV 2019
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A critical analysis of self-supervision, or what we can learn from a single image [pdf] [code]
- Yuki M. Asano, Christian Rupprecht, Andrea Vedaldi. ICLR 2020
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On Mutual Information Maximization for Representation Learning [pdf] [code]
- Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic. ICLR 2020
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Understanding the Limitations of Variational Mutual Information Estimators [pdf] [code]
- Jiaming Song, Stefano Ermon. ICLR 2020
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Self-labelling via simultaneous clustering and representation learning [pdf] [blogpost] [code]
- Yuki Markus Asano, Christian Rupprecht, Andrea Vedaldi. ICLR 2020 (Spotlight)
-
Self-supervised Label Augmentation via Input Transformations [pdf] [code]
- Hankook Lee, Sung Ju Hwang, Jinwoo Shin. ICML 2020
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Automatic Shortcut Removal for Self-Supervised Representation Learning [pdf]
- Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen
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A Simple Framework for Contrastive Learning of Visual Representations [pdf] [code]
- Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey Hinton. ICML 2020
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How Useful is Self-Supervised Pretraining for Visual Tasks? [pdf] [code]
- Alejandro Newell, Jia Deng. CVPR 2020
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Momentum Contrast for Unsupervised Visual Representation Learning [pdf] [code]
- Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, Ross Girshick. CVPR 2020
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ClusterFit: Improving Generalization of Visual Representations [pdf]
- Xueting Yan*, Ishan Misra*, Abhinav Gupta, Deepti Ghadiyaram**, Dhruv Mahajan**. CVPR 2020
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Self-Supervised Learning of Pretext-Invariant Representations [pdf]
- Ishan Misra, Laurens van der Maaten. CVPR 2020
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Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning [pdf] [unofficial-code]
- 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, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko. NeurIPS 2020, Oral
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Contrastive learning of global and local features for medical image segmentation with limited annotations [pdf] [code]
- Krishna Chaitanya, Ertunc Erdil, Neerav Karani, Ender Konukoglu. NeurIPS 2020, Oral
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Unsupervised Representation Learning by InvariancePropagation [pdf] [code]
- Feng Wang, Huaping Liu, Di Guo, Fuchun Sun. NeurIPS 2020, Spotlight
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Big Self-Supervised Models are Strong Semi-Supervised Learners [pdf] [code]
- Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, Geoffrey Hinton. NeurIPS 2020
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Self-Supervised Prototypical Transfer Learning for Few-Shot Classification [pdf] [code]
- Carlos Medina, Arnout Devos, Matthias Grossglauser
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SCAN: Learning to Classify Images without Labels [pdf] [code]
- Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Marc Proesmans, Luc Van Gool. ECCV 2020
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Unsupervised Learning of Visual Features by Contrasting Cluster Assignments [pdf] [code]
- Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, Armand Joulin. NeurIPS 2020
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Self-Supervised Relational Reasoning for Representation Learning [pdf] [code]
- Massimiliano Patacchiola, Amos Storkey. NeurIPS 2020, Spotlight
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Exploring Simple Siamese Representation Learning [pdf] [unofficial-code]
- Xinlei Chen, Kaiming He
-
Online Bag-of-Visual-Words Generation for Unsupervised Representation Learning [pdf] [code]
- Spyros Gidaris, Andrei Bursuc, Gilles Puy, Nikos Komodakis, Matthieu Cord, Patrick Pérez
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Rethinking the Value of Labels for Improving Class-Imbalanced Learning [pdf] [code]
- Yuzhe Yang, Zhi Xu. NeurIPS 2020
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Demystifying contrastive self-supervised learning: Invariances, augmentations and dataset biases [pdf]
- Senthil Purushwalkam, Abhinav Gupta. NeurIPS 2020
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Mitigating embedding and class assignment mismatch in unsupervised image classification [pdf] [code]
- Sungwon Han, Sungwon Park, Sungkyu Park, Sundong Kim, Meeyoung Cha. ECCV 2020
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Self-Supervised Learning Across Domains [pdf]
- Silvia Bucci, Antonio D'Innocente, Yujun Liao, Fabio Maria Carlucci, Barbara Caputo, Tatiana Tommasi. T-PAMI 2021
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Barlow twins: Self-supervised learning via redundancy reduction [pdf] [code]
- Zbontar, J., Jing, L., Misra, I., LeCun, Y., & Deny, S.
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Contrastive Semi-Supervised Learning for 2D Medical Image Segmentation [pdf]
- Prashant Pandey, Ajey Pai, Nisarg Bhatt, Prasenjit Das, Govind Makharia, Prathosh AP, Mausam. MICCAI 2021
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Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning [pdf] [code]
- Zhenda Xie, Yutong Lin, Zheng Zhang, Yue Cao, Stephen Lin, and Han Hu. CVPR 2021
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How Well Do Self-Supervised Models Transfer? [pdf] [code]
- Linus Ericsson, Henry Gouk, Timothy M. Hospedales. CVPR 2021
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Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting.
[code]- Ayan Kumar Bhunia, Pinaki nath Chowdhury, Yongxin Yang, Timothy Hospedales, Tao Xiang, Yi-Zhe Song. CVPR 2021
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SelfAugment: Automatic Augmentation Policies for Self-Supervised Learning [pdf] [code]
- Colorado Reed, Sean Metzger, Aravind Srinivas, Trevor Darrell, Kurt Keutzer. CVPR 2021
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Jigsaw Clustering for Unsupervised Visual Representation Learning [pdf] [code]
- Pengguang Chen, Shu Liu, Jiaya Jia. CVPR 2021
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Improving Unsupervised Image Clustering With Robust Learning [pdf] [code]
- Sungwon Park, Sungwon Han, Sundong Kim, Danu Kim, Sungkyu Park, Seunghoon Hong, Meeyoung Cha. CVPR 2021
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Improving Contrastive Learning by Visualizing Feature Transformation [pdf] [code]
- Rui Zhu*, Bingchen Zhao*, Jingen Liu, Zhenglong Sun, Chang Wen Chen. ICCV 2021 Oral
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Tailoring Self-Supervision for Supervised Learning [pdf] [code]
- WonJun Moon, Ji-Hwan Kim, Jae-Pil Heo. ECCV 2022
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FedX: Unsupervised Federated Learning with Cross Knowledge Distillation [pdf] [code]
- Sungwon Han, Sungwon Park, Fangzhao Wu, Sundong Kim, Chuhan Wu, Xing Xie, Meeyoung Cha. ECCV 2022
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Masked Siamese Networks for Label-Efficient Learning [pdf] [code]
- Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael Rabbat, Nicolas Ballas.
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TriBYOL: Triplet BYOL for Self-Supervised Representation Learning [pdf]
- Guang Li, Ren Togo, Takahiro Ogawa, Miki Haseyama. ICASSP 2022
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Self-Knowledge Distillation based Self-Supervised Learning for Covid-19 Detection from Chest X-Ray Images [pdf]
- Guang Li, Ren Togo, Takahiro Ogawa, Miki Haseyama. ICASSP 2022
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Adaptive Soft Contrastive Learning [pdf] [code]
- Chen Feng, Ioannis Patras. ICPR 2022
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Self-Supervised Visual Representation Learning with Semantic Grouping [pdf] [code]
- Xin Wen, Bingchen Zhao, Anlin Zheng, Xiangyu Zhang, and Xiaojuan Qi. NeurIPS 2022
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VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning [pdf]
- Adrien Bardes, Jean Ponce, Yann LeCun. ICLR 2022
- Inter-Instance Similarity Modeling for Contrastive Learning
[pdf]
[code]
- Chengchao Shen, Dawei Liu, Hao Tang, Zhe Qu, Jianxin Wang.
- Asymmetric Patch Sampling for Contrastive Learning
[pdf]
[code]
- Chengchao Shen, Jianzhong Chen, Shu Wang, Hulin Kuang, Jin Liu, Jianxin Wang.
-
Unsupervised Learning of Video Representations using LSTMs. [pdf] [code]
- Srivastava, Nitish and Mansimov, Elman and Salakhudinov, Ruslan. ICML 2015
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Shuffle and Learn: Unsupervised Learning using Temporal Order Verification. [pdf] [code]
- Ishan Misra, C. Lawrence Zitnick and Martial Hebert. ECCV 2016
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LSTM Self-Supervision for Detailed Behavior Analysis [pdf]
- Biagio Brattoli*, Uta Büchler*, Anna-Sophia Wahl, Martin E. Schwab, and Björn Ommer. CVPR 2017
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Self-Supervised Video Representation Learning With Odd-One-Out Networks. [pdf]
- Basura Fernando and Hakan Bilen and Efstratios Gavves and Stephen Gould. CVPR 2017
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Unsupervised Learning of Long-Term Motion Dynamics for Videos. [pdf]
- Luo, Zelun and Peng, Boya and Huang, De-An and Alahi, Alexandre and Fei-Fei, Li. CVPR 2017
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Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning. [pdf]
- Chuang Gan and Boqing Gong and Kun Liu and Hao Su and Leonidas J. Guibas. CVPR 2018
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Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning. [pdf]
- Biagio Brattoli*, Uta Büchler*, and Björn Ommer. ECCV 2018
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Self-supervised learning of a facial attribute embedding from video. [pdf]
- Wiles, O., Koepke, A.S., Zisserman, A. BMVC 2018
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Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles. [pdf]
- Kim, Dahun and Cho, Donghyeon and Yoo, Donggeun and Kweon, In So. AAAI 2019
-
Self-Supervised Spatio-Temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics. [pdf]
- Jiangliu Wang; Jianbo Jiao; Linchao Bao; Shengfeng He; Yunhui Liu; Wei Liu. CVPR 2019
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DynamoNet: Dynamic Action and Motion Network. [pdf]
- Ali Diba; Vivek Sharma, Luc Van Gool, Rainer Stiefelhagen. ICCV 2019
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Learning Correspondence from the Cycle-consistency of Time. [pdf] [code]
- Xiaolong Wang*, Allan Jabri* and Alexei A. Efros. CVPR 2019
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Joint-task Self-supervised Learning for Temporal Correspondence. [pdf] [code]
- Xueting Li*, Sifei Liu*, Shalini De Mello, Xiaolong Wang, Jan Kautz, and Ming-Hsuan Yang. NIPS 2019
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Self-Supervised Video Representation Learning Using Inter-Intra Contrstive Framework [pdf] [code]
- Li Tao, Xueting Wang*, Toshihiko Yamasaki. ACMMM 2020
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Video Playback Rate Perception for Self-Supervised Spatio-Temporal Representation Learning [pdf] [Code]
- Yuan Yao*, Chang Liu*, Dezhao Luo, Yu Zhou, Qixiang Ye. CVPR 2020
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Self-Supervised Video Representation Learning by Pace Prediction [pdf] [code]
- Jiangliu Wang, Jianbo Jiao, Yun-Hui Liu. ECCV 2020
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Video Representation Learning by Recognizing Temporal Transformations [pdf] [code]
- Simon Jenni, Givi Meishvili, Paolo Favaro. ECCV 2020
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Self-supervised Co-training for Video Representation Learning [pdf] [code]
- Tengda Han, Weidi Xie, and Andrew Zisserman. NeurIPS 2020
-
Cycle-Contrast for Self-Supervised Video Representation Learning [pdf]
- Quan Kong, Wenpeng Wei, Ziwei Deng, Tomoaki Yoshinaga, and Tomokazu Murakami. NeurIPS 2020
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Video Representation Learning with Visual Tempo Consistency [pdf] [code]
- Ceyuan Yang, Yinghao Xu, Bo Dai, and Bolei Zhou
-
Self-supervised Video Representation Learning by Uncovering Spatio-temporal Statistics [pdf]
- Jiangliu Wang, Jianbo Jiao, Linchao Bao, Shengfeng He, Wei Liu, and Yun-hui Liu
-
Spatiotemporal Contrastive Video Representation Learning [pdf]
- Rui Qian, Tianjian Meng, Boqing Gong, Ming-Hsuan Yang, Huisheng Wang, Serge Belongie, and Yin Cui
-
Self-Supervised Video Representation Using Pretext-Contrastive Learning [pdf]
- Li Tao, Xueting Wang, and Toshihiko Yamasaki
-
Unsupervised Video Representation Learning by Bidirectional Feature Prediction [pdf]
- Nadine Behrmann, Juergen Gall, and Mehdi Noroozi
-
RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning [pdf] [code]
- Peihao Chen, Deng Huang, Dongliang He, Xiang Long, Runhao Zeng, Shilei Wen, Mingkui Tan, and Chuang Gan. AAAI 2021
-
Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning [pdf]
- Zehua Zhang and David Crandall
-
Can Temporal Information Help with Contrastive Self-Supervised Learning? [pdf]
- Yutong Bai, Haoqi Fan, Ishan Misra, Ganesh Venkatesh, Yongyi Lu, Yuyin Zhou, Qihang Yu, Vikas Chandra, and Alan Yuille
-
Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion [pdf] [code]
- Jinpeng Wang, Yuting Gao, Ke Li, Jianguo Hu, Xinyang Jiang, Xiaowei Guo, Rongrong Ji, and Xing Sun. AAAI 2021
-
Space-Time Correspondence as a Contrastive Random Walk [pdf] [code] [project]
- Allan Jabri, Andrew Owens, Alexei A. Efros. NeurIPS 2020 Oral
- How Severe is Benchmark-Sensitivity in Video Self-Supervised Learning?
[pdf]
[code]
- Thoker, Fida Mohammad and Doughty, Hazel and Bagad, Piyush and Snoek, Cees . ECCV 2022
-
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space [pdf]
- Jonathan Sauder, and Bjarne Sievers NeurIPS 2019
-
Self-Supervised Learning of Point Clouds via Orientation Estimation [pdf] [code]
- Omid Poursaeed, Tianxing Jiang, Han Qiao, Nayun Xu, and Vladimir G. Kim,3DV 2020
-
Self-Supervised Learning on 3D Point Clouds by Learning Discrete Generative Models [pdf]
- Benjamin Eckart, Wentao Yuan, Chao Liu, and Jan Kautz CVPR 2021
-
PointContrast: Unsupervised Pre-training for 3D Point Cloud [pdf] [code]
- Saining Xie, Jiatao Gu, Demi Guo, Charles R. Qi, Leonidas Guibas, and Or Litany ECCV 2020
-
Guided Point Contrastive Learning for Semi-supervised Point Cloud Semantic Segmentation [pdf]
- Li Jiang, Shaoshuai Shi, Zhuotao Tian, Xin Lai, Shu Liu, Chi-Wing Fu, and Jiaya Jia ICCV 2021
-
Ponder: Point Cloud Pre-training via Neural Rendering [pdf]
- Di Huang, Sida Peng, Tong He, Honghui Yang, Xiaowei Zhou and Wanli Ouyang ICCV 2023
-
PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm [pdf] [code]
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To the extent possible under law, Zhongzheng Ren has waived all copyright and related or neighboring rights to this work.