{"id":34975,"url":"https://github.com/eric-erki/awesome-self-supervised-learning","name":"awesome-self-supervised-learning","description":"A curated list of awesome self-supervised methods","projects_count":208,"last_synced_at":"2026-07-29T15:00:19.547Z","repository":{"id":99091032,"uuid":"237763879","full_name":"eric-erki/awesome-self-supervised-learning","owner":"eric-erki","description":"A curated list of awesome self-supervised methods","archived":false,"fork":false,"pushed_at":"2020-02-02T11:55:51.000Z","size":70,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2026-07-10T15:03:13.475Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/eric-erki.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2020-02-02T11:55:23.000Z","updated_at":"2020-02-02T11:56:00.000Z","dependencies_parsed_at":"2023-07-05T12:46:17.487Z","dependency_job_id":null,"html_url":"https://github.com/eric-erki/awesome-self-supervised-learning","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/eric-erki/awesome-self-supervised-learning","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eric-erki%2Fawesome-self-supervised-learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eric-erki%2Fawesome-self-supervised-learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eric-erki%2Fawesome-self-supervised-learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eric-erki%2Fawesome-self-supervised-learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/eric-erki","download_url":"https://codeload.github.com/eric-erki/awesome-self-supervised-learning/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eric-erki%2Fawesome-self-supervised-learning/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":36037223,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-07-20T02:08:10.276Z","status":"online","status_checked_at":"2026-07-29T02:00:04.910Z","response_time":95,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-13T12:59:13.487Z","updated_at":"2026-07-29T15:00:19.547Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["NLP","Computer Vision","Contributing","Machine Learning","Robotics","Talks","Thesis","Blog"],"sub_categories":["2019","Image Representation Learning","Survey","Video Representation Learning","Geometry","Audio","Others","Reinforcement Learning","2006","2009","2014","2015","2016","2017","2018","2012"],"readme":"# Awesome Self-Supervised Learning[![Awesome](https://awesome.re/badge.svg)](https://awesome.re)\n\n\u003cp align=\"center\"\u003e\n  \u003cimg width=\"250\" src=\"https://camo.githubusercontent.com/1131548cf666e1150ebd2a52f44776d539f06324/68747470733a2f2f63646e2e7261776769742e636f6d2f73696e647265736f726875732f617765736f6d652f6d61737465722f6d656469612f6c6f676f2e737667\" \"Awesome!\"\u003e\n\u003c/p\u003e\n\nA curated list of awesome Self-Supervised Learning resources. Inspired by [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision), [awesome-adversarial-machine-learning](https://github.com/yenchenlin/awesome-adversarial-machine-learning), [awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers), and [awesome-architecture-search](https://github.com/markdtw/awesome-architecture-search)\n\n#### Why Self-Supervised?\nSelf-Supervised Learning has become an exciting direction in AI community. \n  - Jitendra Malik: \"Supervision is the opium of the AI researcher\"\n  - Alyosha Efros: \"The AI revolution will not be supervised\"\n  - Yann LeCun: \"self-supervised learning is the cake, supervised learning is the icing on the cake, reinforcement learning is the cherry on the cake\"\n\n## Contributing\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"http://cdn1.sportngin.com/attachments/news_article/7269/5172/needyou_small.jpg\" alt=\"We Need You!\"\u003e\n\u003c/p\u003e\n\nPlease help contribute this list by contacting [me](https://jason718.github.io/) or add [pull request](https://github.com/jason718/Awesome-Self-Supervised-Learning/pulls)\n\nMarkdown format:\n```markdown\n- Paper Name. \n  [[pdf]](link) \n  [[code]](link)\n  - Author 1, Author 2, and Author 3. *Conference Year*\n```\n\n## Table of Contents\n- [Computer Vision (CV)](#computer-vision)\n  - [Survey](#survey)\n  - [Image Representation Learning](#image-representation-learning)\n  - [Video Representation Learning](#video-representation-learning)\n  - [Geometry](#geometry)\n  - [Audio](#audio)\n  - [Others](#others)\n- [Machine Learning](#machine-learning)\n  - [Reinforcement Learning](#reinforcement-learning)\n- [Robotics](#robotics)  \n- [Natural Language Processing (NLP)](#nlp)  \n- [Talks](#talks)\n- [Thesis](#thesis)\n\n## Computer Vision\n### Survey\n- Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey.\n  [[pdf]](https://arxiv.org/pdf/1902.06162.pdf)\n  - Longlong Jing and Yingli Tian.\n\n\n### Image Representation Learning\n\n#### Benchmark code\nFAIR Self-Supervision Benchmark [[repo]](https://github.com/facebookresearch/fair_self_supervision_benchmark): various benchmark (and legacy) tasks for evaluating quality of visual representations learned by various self-supervision approaches. \n\n#### 2015\n- Unsupervised Visual Representation Learning by Context Prediction.\n  [[pdf]](https://arxiv.org/abs/1505.05192)\n  [[code]](http://graphics.cs.cmu.edu/projects/deepContext/)\n  - Doersch, Carl and Gupta, Abhinav and Efros, Alexei A. *ICCV 2015*\n\n- Unsupervised Learning of Visual Representations using Videos.\n  [[pdf]](http://www.cs.cmu.edu/~xiaolonw/papers/unsupervised_video.pdf) \n  [[code]](http://www.cs.cmu.edu/~xiaolonw/unsupervise.html)\n  - Wang, Xiaolong and Gupta, Abhinav. *ICCV 2015*\n\n- Learning to See by Moving. \n  [[pdf]](http://arxiv.org/abs/1505.01596)\n  [[code]](https://people.eecs.berkeley.edu/~pulkitag/lsm/lsm.html)\n  - Agrawal, Pulkit and Carreira, Joao and Malik, Jitendra. *ICCV 2015*\n\n- Learning image representations tied to ego-motion.\n  [[pdf]](http://vision.cs.utexas.edu/projects/egoequiv/ijcv_bestpaper_specialissue_egoequiv.pdf) \n  [[code]](http://vision.cs.utexas.edu/projects/egoequiv/)\n  - Jayaraman, Dinesh and Grauman, Kristen. *ICCV 2015*\n\n#### 2016\n- Joint Unsupervised Learning of Deep Representations and Image Clusters. \n  [[pdf]](https://arxiv.org/pdf/1604.03628.pdf) \n  [[code-torch]](https://github.com/jwyang/JULE.torch)\n  [[code-caffe]](https://github.com/jwyang/JULE-Caffe)\n  - Jianwei Yang, Devi Parikh, Dhruv Batra. *CVPR 2016*\n  \n- Unsupervised Deep Embedding for Clustering Analysis.\n  [[pdf]](https://arxiv.org/pdf/1511.06335.pdf) \n  [[code]](https://github.com/piiswrong/dec)\n  - Junyuan Xie, Ross Girshick, and Ali Farhadi. *ICML 2016*\n  \n- Slow and steady feature analysis: higher order temporal coherence in video. \n  [[pdf]](http://vision.cs.utexas.edu/projects/slowsteady/cvpr16.pdf)\n  - Jayaraman, Dinesh and Grauman, Kristen. *CVPR 2016*\n\n- Context Encoders: Feature Learning by Inpainting. \n  [[pdf]](https://people.eecs.berkeley.edu/~pathak/papers/cvpr16.pdf)\n  [[code]](https://people.eecs.berkeley.edu/~pathak/context_encoder/)\n  - Pathak, Deepak and  Krahenbuhl, Philipp and Donahue, Jeff and Darrell, Trevor and Efros, Alexei A. *CVPR 2016*\n\n- Colorful Image Colorization.\n  [[pdf]](https://arxiv.org/abs/1603.08511)\n  [[code]](http://richzhang.github.io/colorization/)\n  - Zhang, Richard and Isola, Phillip and Efros, Alexei A. *ECCV 2016*\n\n- Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles.\n  [[pdf]](http://arxiv.org/abs/1603.09246)\n  [[code]](http://www.cvg.unibe.ch/research/JigsawPuzzleSolver.html)\n  - Noroozi, Mehdi and Favaro, Paolo. *ECCV 2016*\n\n- Ambient Sound Provides Supervision for Visual Learning.\n  [[pdf]](http://arxiv.org/pdf/1608.07017) \n  [[code]](http://andrewowens.com/ambient/index.html)\n  - Owens, Andrew and Wu, Jiajun and McDermott, Josh and Freeman, William and Torralba, Antonio. *ECCV 2016*\n\n- Learning Representations for Automatic Colorization. \n  [[pdf]](http://arxiv.org/pdf/1603.06668.pdf)\n  [[code]](http://people.cs.uchicago.edu/~larsson/colorization/)\n  - Larsson, Gustav and Maire, Michael and Shakhnarovich, Gregory. *ECCV 2016*\n\n-   Unsupervised Visual Representation Learning by Graph-based Consistent Constraints.\n    [\\[pdf\\]](http://faculty.ucmerced.edu/mhyang/papers/eccv16_feature_learning.pdf)\n    [\\[code\\]](https://github.com/dongli12/FeatureLearning)\n    -   Li, Dong and Hung, Wei-Chih and Huang, Jia-Bin and Wang, Shengjin and Ahuja, Narendra and Yang, Ming-Hsuan. *ECCV 2016*\n\n#### 2017\n- Adversarial Feature Learning. \n  [[pdf]](https://arxiv.org/pdf/1605.09782.pdf)\n  [[code]](https://github.com/jeffdonahue/bigan)\n  - Donahue, Jeff and Krahenbuhl, Philipp and Darrell, Trevor. *ICLR 2017*\n  \n- Self-supervised learning of visual features through embedding images into text topic spaces.\n  [[pdf]](https://arxiv.org/pdf/1705.08631.pdf)\n  [[code]](https://github.com/lluisgomez/TextTopicNet)\n  - L. Gomez* and Y. Patel* and M. Rusiñol and D. Karatzas and C.V. Jawahar. *CVPR 2017*\n  \n- Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction.\n  [[pdf]](https://arxiv.org/abs/1611.09842) \n  [[code]](https://github.com/richzhang/splitbrainauto)\n  - Zhang, Richard and Isola, Phillip and Efros, Alexei A. *CVPR 2017*\n\n- Learning Features by Watching Objects Move.\n  [[pdf]](https://people.eecs.berkeley.edu/~pathak/papers/cvpr17.pdf) \n  [[code]](https://people.eecs.berkeley.edu/~pathak/unsupervised_video/)\n  - Pathak, Deepak and Girshick, Ross and Dollar, Piotr and  Darrell, Trevor and Hariharan, Bharath. *CVPR 2017*\n  \n- Colorization as a Proxy Task for Visual Understanding. \n  [[pdf]](http://arxiv.org/abs/1703.04044) \n  [[code]](http://people.cs.uchicago.edu/~larsson/color-proxy/)\n  - Larsson, Gustav and Maire, Michael and Shakhnarovich, Gregory. *CVPR 2017*\n\n-   DeepPermNet: Visual Permutation Learning.\n    [\\[pdf\\]](https://arxiv.org/pdf/1704.02729.pdf)\n    [\\[code\\]](https://github.com/rfsantacruz/deep-perm-net)\n    -   Cruz, Rodrigo Santa and Fernando, Basura and Cherian, Anoop and Gould, Stephen. *CVPR 2017*\n\n- Unsupervised Learning by Predicting Noise.\n  [[pdf]](https://arxiv.org/abs/1704.05310) \n  [[code]](https://github.com/facebookresearch/noise-as-targets)\n  - Bojanowski, Piotr and Joulin, Armand. *ICML 2017*\n\n- Multi-task Self-Supervised Visual Learning. \n  [[pdf]](https://arxiv.org/abs/1708.07860)\n  - Doersch, Carl and Zisserman, Andrew. *ICCV 2017*\n\n- Representation Learning by Learning to Count.\n  [[pdf]](https://arxiv.org/abs/1708.06734)\n  - Noroozi, Mehdi and Pirsiavash, Hamed and Favaro, Paolo. *ICCV 2017*\n\n- Transitive Invariance for Self-supervised Visual Representation Learning.\n  [[pdf]](https://arxiv.org/pdf/1708.02901.pdf)\n  - Wang, Xiaolong and He, Kaiming and Gupta, Abhinav. *ICCV 2017*\n\n- Look, Listen and Learn. \n  [[pdf]](https://arxiv.org/pdf/1705.08168.pdf)\n  - Relja, Arandjelovic and Zisserman, Andrew. *ICCV 2017*\n\n- Unsupervised Representation Learning by Sorting Sequences. \n  [[pdf]](https://arxiv.org/pdf/1708.01246.pdf) \n  [[code]](https://github.com/HsinYingLee/OPN)\n  - Hsin-Ying Lee, Jia-Bin Huang, Maneesh Kumar Singh, and Ming-Hsuan Yang. *ICCV 2017*\n\n#### 2018\n\n- Unsupervised Feature Learning via Non-parameteric Instance Discrimination\n  [[pdf]](https://arxiv.org/pdf/1805.01978.pdf) \n  [[code]](https://github.com/zhirongw/lemniscate.pytorch)\n  - Zhirong Wu, Yuanjun Xiong and X Yu Stella and Dahua Lin. *CVPR 2018*\n\n- Learning Image Representations by Completing Damaged Jigsaw Puzzles. \n  [[pdf]](https://arxiv.org/pdf/1802.01880.pdf)\n  - Kim, Dahun and Cho, Donghyeon and Yoo, Donggeun and Kweon, In So. *WACV 2018*\n  \n- Unsupervised Representation Learning by Predicting Image Rotations. \n  [[pdf]](https://openreview.net/forum?id=S1v4N2l0-)\n  [[code]](https://github.com/gidariss/FeatureLearningRotNet)\n  - Spyros Gidaris and Praveer Singh and Nikos Komodakis. *ICLR 2018*\n  \n- Improvements to context based self-supervised learning. \n  [[pdf]](https://arxiv.org/abs/1711.06379)\n  - Terrell Mundhenk and Daniel Ho and Barry Chen. *CVPR 2018*\n  \n- Self-Supervised Feature Learning by Learning to Spot Artifacts.\n  [[pdf]](https://arxiv.org/pdf/1806.05024.pdf)\n  [[code]](https://github.com/sjenni/LearningToSpotArtifacts)\n  - Simon Jenni and Universität Bern and Paolo Favaro. *CVPR 2018*\n  \n- Boosting Self-Supervised Learning via Knowledge Transfer. \n  [[pdf]](https://www.csee.umbc.edu/~hpirsiav/papers/transfer_cvpr18.pdf)\n  - Mehdi Noroozi and Ananth Vinjimoor and Paolo Favaro and Hamed Pirsiavash. *CVPR 2018*\n  \n- Cross-domain Self-supervised Multi-task Feature Learning Using Synthetic Imagery. \n  [[pdf]](https://arxiv.org/abs/1711.09082)\n  [[code]](https://github.com/jason718/game-feature-learning)\n  - Zhongzheng Ren and Yong Jae Lee. *CVPR 2018*\n  \n- ShapeCodes: Self-Supervised Feature Learning by Lifting Views to Viewgrids.\n  [[pdf]](https://arxiv.org/pdf/1709.00505.pdf)\n  - Dinesh Jayaraman*, UC Berkeley; Ruohan Gao, University of Texas at Austin; Kristen Grauman. *ECCV 2018*\n\n- Deep Clustering for Unsupervised Learning of Visual Features\n    [[pdf]](https://research.fb.com/wp-content/uploads/2018/09/Deep-Clustering-for-Unsupervised-Learning-of-Visual-Features.pdf)\n    - Mathilde Caron, Piotr Bojanowski, Armand Joulin, Matthijs Douze. *ECCV 2018*\n\n- Cross Pixel Optical-Flow Similarity for Self-Supervised Learning.\n  [[pdf]](http://www.robots.ox.ac.uk/~vgg/publications/2018/Mahendran18/mahendran18.pdf)\n  - Aravindh Mahendran, James Thewlis, Andrea Vedaldi. *ACCV 2018*\n\n#### 2019\n\n- Representation Learning with Contrastive Predictive Coding.\n  [[pdf]](https://arxiv.org/abs/1807.03748)\n  - Aaron van den Oord, Yazhe Li, Oriol Vinyals.\n\n- Self-Supervised Learning via Conditional Motion Propagation.\n  [[pdf]](http://www.robots.ox.ac.uk/~vgg/publications/2018/Mahendran18/mahendran18.pdf)\n  [[code]](https://github.com/XiaohangZhan/conditional-motion-propagation)\n  - Xiaohang Zhan, Xingang Pan, Ziwei Liu, Dahua Lin, and Chen Change Loy. *CVPR 2019*\n\n- Self-Supervised Representation Learning by Rotation Feature Decoupling.\n  [[pdf]](http://openaccess.thecvf.com/content_CVPR_2019/html/Feng_Self-Supervised_Representation_Learning_by_Rotation_Feature_Decoupling_CVPR_2019_paper.html)\n  [[code]](https://github.com/philiptheother/FeatureDecoupling)\n  - Zeyu Feng; Chang Xu; Dacheng Tao. *CVPR 2019*\n\n- Revisiting Self-Supervised Visual Representation Learning.\n  [[pdf]](https://arxiv.org/abs/1901.09005)\n  [[code]](https://github.com/google/revisiting-self-supervised)\n  - Alexander Kolesnikov; Xiaohua Zhai; Lucas Beye. CVPR 2019\n\n- AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data.\n  [[pdf]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_AET_vs._AED_Unsupervised_Representation_Learning_by_Auto-Encoding_Transformations_Rather_CVPR_2019_paper.pdf)\n  [[code]](https://github.com/maple-research-lab/AET)\n  - Liheng Zhang, Guo-Jun Qi, Liqiang Wang, Jiebo Luo. *CVPR 2019*\n\n- Unsupervised Deep Learning by Neighbourhood Discovery.\n  [[pdf]](http://proceedings.mlr.press/v97/huang19b.html).\n  [[code]](https://github.com/Raymond-sci/AND).\n  - Jiabo Huang, Qi Dong, Shaogang Gong, Xiatian Zhu. *ICML 2019*\n  \n- Contrastive Multiview Coding.\n  [[pdf]](https://arxiv.org/abs/1906.05849)\n  [[code]](https://github.com/HobbitLong/CMC/)\n  - Yonglong Tian and Dilip Krishnan and Phillip Isola.\n\n- Large Scale Adversarial Representation Learning.\n  [[pdf]](https://arxiv.org/abs/1907.02544)\n  - Jeff Donahue, Karen Simonyan.\n\n- Learning Representations by Maximizing Mutual Information Across Views.\n  [[pdf]](https://arxiv.org/pdf/1906.00910)\n  - Philip Bachman, R Devon Hjelm, William Buchwalter\n\n - Selfie: Self-supervised Pretraining for Image Embedding. \n    [[pdf]](https://arxiv.org/abs/1906.02940) \n    - Trieu H. Trinh, Minh-Thang Luong, Quoc V. Le\n   \n - Data-Efficient Image Recognition with Contrastive Predictive Coding\n    [[pdf]](https://arxiv.org/abs/1905.09272)\n    - Olivier J. He ́naff, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aaron van den Oord\n\n - Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty\n    [[pdf]](https://arxiv.org/pdf/1906.12340)\n    [[code]](https://github.com/hendrycks/ss-ood)\n    - Dan Hendrycks, Mantas Mazeika, Saurav Kadavath, Dawn Song. *NeurIPS 2019*\n\n - Momentum Contrast for Unsupervised Visual Representation Learning\n    [[pdf]](https://arxiv.org/pdf/1911.05722.pdf)\n    - Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, Ross Girshick. *FAIR*\n\n### Video Representation Learning\n\n- Unsupervised Learning of Video Representations using LSTMs.\n  [[pdf]](https://arxiv.org/pdf/1502.04681.pdf)\n  [[code]](https://github.com/emansim/unsupervised-videos)\n  - Srivastava, Nitish and Mansimov, Elman and Salakhudinov, Ruslan. *ICML 2015*\n\n- Shuffle and Learn: Unsupervised Learning using Temporal Order Verification. \n  [[pdf]](http://arxiv.org/abs/1603.08561) \n  [[code]](https://github.com/imisra/shuffle-tuple)\n  - Ishan Misra, C. Lawrence Zitnick and Martial Hebert. *ECCV 2016*\n  \n- LSTM Self-Supervision for Detailed Behavior Analysis\n  [[pdf]](http://openaccess.thecvf.com/content_cvpr_2017/papers/Brattoli_LSTM_Self-Supervision_for_CVPR_2017_paper.pdf)\n  - Biagio Brattoli*, Uta Büchler*, Anna-Sophia Wahl, Martin E. Schwab, and Björn Ommer. *CVPR 2017*\n  \n- Self-Supervised Video Representation Learning With Odd-One-Out Networks. \n  [[pdf]](https://arxiv.org/abs/1611.06646) \n  - Basura Fernando and Hakan Bilen and Efstratios Gavves and Stephen Gould. *CVPR 2017*\n\n- Unsupervised Learning of Long-Term Motion Dynamics for Videos. \n  [[pdf]](https://arxiv.org/pdf/1701.01821.pdf)\n  - Luo, Zelun and Peng, Boya and Huang, De-An and Alahi, Alexandre and Fei-Fei, Li. *CVPR 2017*\n\n- Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning.\n  [[pdf]](http://ai.ucsd.edu/~haosu/papers/cvpr18_geometry_predictive_learning.pdf) \n  - Chuang Gan and Boqing Gong and Kun Liu and Hao Su and Leonidas J. Guibas. *CVPR 2018*\n  \n- Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning.\n  [[pdf]](https://arxiv.org/abs/1807.11293)\n  - Biagio Brattoli*, Uta Büchler*, and Björn Ommer. *ECCV 2018*\n\n- Self-supervised learning of a facial attribute embedding from video.\n  [[pdf]](http://www.robots.ox.ac.uk/~vgg/publications/2018/Wiles18a/wiles18a.pdf)\n  - Wiles, O.*, Koepke, A.S.*, Zisserman, A. *BMVC 2018*\n\n- Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles. \n  [[pdf]](https://arxiv.org/pdf/1811.09795.pdf)\n  - Kim, Dahun and Cho, Donghyeon and Yoo, Donggeun and Kweon, In So. *AAAI 2019*\n\n- Self-Supervised Spatio-Temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics.\n  [[pdf]](https://arxiv.org/abs/1904.03597)\n  - Jiangliu Wang; Jianbo Jiao; Linchao Bao; Shengfeng He; Yunhui Liu; Wei Liu. CVPR 2019\n\n- DynamoNet: Dynamic Action and Motion Network.\n  [[pdf]](https://arxiv.org/pdf/1904.11407.pdf)\n  - Ali Diba; Vivek Sharma, Luc Van Gool, Rainer Stiefelhagen. *ICCV 2019*\n\n- Learning Correspondence from the Cycle-consistency of Time.\n  [[pdf]](https://arxiv.org/abs/1903.07593) \n  [[code]](https://github.com/xiaolonw/TimeCycle)\n  - Xiaolong Wang*, Allan Jabri* and Alexei A. Efros. *CVPR 2019*\n\n- Joint-task Self-supervised Learning for Temporal Correspondence.\n  [[pdf]](https://arxiv.org/abs/1909.11895) \n  [[code]](https://github.com/Liusifei/UVC)\n  - Xueting Li*, Sifei Liu*, Shalini De Mello, Xiaolong Wang, Jan Kautz, and Ming-Hsuan Yang. *NIPS 2019*\n\n### Geometry\n-   Self-supervised Learning of Motion Capture.\n    [[pdf]](https://arxiv.org/pdf/1712.01337.pdf)\n    [[code]](https://github.com/htung0101/3d_smpl)\n    [[web]](https://sites.google.com/view/selfsupervisedlearningofmotion/)\n    -   Tung, Hsiao-Yu and Tung, Hsiao-Wei and Yumer, Ersin and Fragkiadaki, Katerina. *NIPS 2017*\n\n-   Unsupervised Learning of Depth and Ego-Motion from Video. \n    [[pdf]](https://arxiv.org/pdf/1704.07813.pdf)\n    [[code]](https://github.com/tinghuiz/SfMLearner)\n    [[web]](https://people.eecs.berkeley.edu/~tinghuiz/projects/SfMLearner/)\n    -   Zhou, Tinghui and Brown, Matthew and Snavely, Noah and Lowe, David G. *CVPR 2017*\n    \n- Active Stereo Net: End-to-End Self-Supervised Learning for Active Stereo Systems.\n  [[project]](http://asn.cs.princeton.edu/)\n  - Yinda Zhang*, Sean Fanello, Sameh Khamis, Christoph Rhemann, Julien Valentin, Adarsh Kowdle, Vladimir Tankovich, Shahram Izadi, Thomas Funkhouser. *ECCV 2018*\n\n- Self-Supervised Relative Depth Learning for Urban Scene Understanding.\n  [[pdf]](https://people.cs.umass.edu/~hzjiang/files/ssr_depth.pdf)\n  [[project]](https://people.cs.umass.edu/~hzjiang/projects/ssr_depth/)\n  - Huaizu Jiang*, Erik Learned-Miller, Gustav Larsson, Michael Maire, Greg Shakhnarovich. *ECCV 2018*\n\n- Geometry-Aware Learning of Maps for Camera Localization.\n  [[pdf]](https://arxiv.org/abs/1712.03342)\n  [[code]](https://github.com/NVlabs/geomapnet)\n  - Samarth Brahmbhatt, Jinwei Gu, Kihwan Kim, James Hays, and Jan Kautz. CVPR 2018\n\n- Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection.\n  [[pdf]](https://arxiv.org/abs/1804.01552)\n  [[web]](http://www.robots.ox.ac.uk/~vgg/research/probabilistic_introspection/)\n  - David Novotny, Samuel Albanie, Diane Larlus, Andrea Vedaldi. CVPR 2018\n\n- Self-Supervised Learning of 3D Human Pose Using Multi-View Geometry.\n  [[pdf]](https://arxiv.org/abs/1903.02330)\n  - Muhammed Kocabas; Salih Karagoz; Emre Akbas. CVPR 2019\n\n- SelFlow: Self-Supervised Learning of Optical Flow.\n  [[pdf]](https://arxiv.org/abs/1904.03597)\n  - Jiangliu Wang; Jianbo Jiao; Linchao Bao; Shengfeng He; Yunhui Liu; Wei Liu. CVPR 2019\n\n- Unsupervised Learning of Landmarks by Descriptor Vector Exchange.\n  [[pdf]](https://arxiv.org/abs/1908.06427)\n  [[code]](https://github.com/jamt9000/DVE)\n  [[web]](http://www.robots.ox.ac.uk/~vgg/research/DVE/)\n  - James Thewlis, Samuel Albanie, Hakan Bilen, Andrea Vedaldi. ICCV 2019\n\n \n\n### Audio\n- Audio-Visual Scene Analysis with Self-Supervised Multisensory Features.\n  [[pdf]](https://arxiv.org/pdf/1804.03641.pdf)\n  [[code]](https://github.com/andrewowens/multisensory)\n  - Andrew Owens, Alexei A. Efros. *ECCV 2018*\n  \n- Objects that Sound.\n  [[pdf]](https://arxiv.org/pdf/1712.06651.pdf)\n  -  R. Arandjelović, A. Zisserman. *ECCV 2018* \n  \n- Learning to Separate Object Sounds by Watching Unlabeled Video.\n  [[pdf]](https://arxiv.org/abs/1804.01665)\n  [[project]](http://vision.cs.utexas.edu/projects/separating_object_sounds/)\n  - Ruohan Gao, Rogerio Feris, Kristen Grauman.  *ECCV 2018*\n  \n- The Sound of Pixels.\n  [[pdf]]( https://arxiv.org/pdf/1907.11879.pdf )\n  [[project]](https://github.com/hangzhaomit/Sound-of-Pixels)\n  - Zhao, Hang and Gan, Chuang and Rouditchenko, Andrew and Vondrick, Carl and McDermott, Josh and Torralba, Antonio. *ECCV 2018*\n\n- Learnable PINs: Cross-Modal Embeddings for Person Identity.\n  [[pdf]](https://arxiv.org/abs/1805.00833)\n  [[web]](http://www.robots.ox.ac.uk/~vgg/research/LearnablePins/)\n  - Arsha Nagrani, Samuel Albanie, Andrew Zisserman. ECCV 2018\n\n\n- Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization. \n  [[pdf]](http://papers.nips.cc/paper/8002-cooperative-learning-of-audio-and-video-models-from-self-supervised-synchronization.pdf)\n  - Bruno Korbar,Dartmouth College, Du Tran, Lorenzo Torresani. *NIPS 2018*\n  \n- Self-Supervised Generation of Spatial Audio for 360° Video.\n  [[pdf]](http://papers.nips.cc/paper/7319-self-supervised-generation-of-spatial-audio-for-360-video.pdf)\n  - Pedro Morgado, Nuno Nvasconcelos, Timothy Langlois, Oliver Wang. *NIPS 2018*\n  \n- TriCycle: Audio Representation Learning from Sensor Network Data Using Self-Supervision\n  [[pdf]](http://www.justinsalamon.com/uploads/4/3/9/4/4394963/cartwright_tricycle_waspaa2019.pdf)\n  - Mark Cartwright, Jason Cramer, Justin Salamon, Juan Pablo Bello. *WASPAA 2019*\n\n### Others\n- Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model.\n  [[pdf]](https://arxiv.org/abs/1611.07544)\n  - Qixiang Ye, Tianliang Zhang, Qiang Qiu, Baochang Zhang, Jie Chen, Guillermo Sapiro. *CVPR 2017*\n- Free Supervision from Video Games.\n  [[pdf]](http://www.philkr.net/papers/2018-06-01-cvpr/2018-06-01-cvpr.pdf)\n  [[project+code]](http://www.philkr.net/fsv/)\n  - Philipp Krähenbühl. *CVPR 2018*\n- Fighting Fake News: Image Splice Detection via Learned Self-Consistency\n  [[pdf]](https://arxiv.org/pdf/1805.04096.pdf)\n  [[code]](https://github.com/minyoungg/selfconsistency)\n  - Minyoung Huh*, Andrew Liu*, Andrew Owens, Alexei A. Efros. *ECCV 2018*\n- Self-supervised Tracking by Colorization (Tracking Emerges by Colorizing Videos).\n  [[pdf]](https://www.cs.columbia.edu/~vondrick//videocolor.pdf)\n  - Carl Vondrick*, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama, Kevin Murphy. *ECCV 2018*\n- High-Fidelity Image Generation With Fewer Labels.\n  [[pdf]](https://arxiv.org/pdf/1903.02271.pdf)\n  - Mario Lucic*, Michael Tschannen*, Marvin Ritter*, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly.\n- Self-supervised Fitting of Articulated Meshes to Point Clouds.\n  - Chun-Liang Li, Tomas Simon, Jason Saragih, Barnabás Póczos and Yaser Sheikh. *CVPR 2019*\n- SCOPS: Self-Supervised Co-Part Segmentation. \n  - Wei-Chih Hung, Varun Jampani, Sifei Liu, Pavlo Molchanov, Ming-Hsuan Yang, and Jan Kautz. *CVPR 2019*\n- Self-Supervised GANs via Auxiliary Rotation Loss. \n  - Ting Chen; Xiaohua Zhai; Marvin Ritter; Mario Lucic; Neil Houlsby. *CVPR 2019*\n- Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking.\n  - Jae Shin Yoon; Takaaki Shiratori; Shoou-I Yu; Hyun Soo Park. *CVPR 2019*\n- Multi-Task Self-Supervised Object Detection via Recycling of Bounding Box Annotations.\n  - Wonhee Lee; Joonil Na; Gunhee Kim. *CVPR 2019*\n- Self-Supervised Convolutional Subspace Clustering Network.\n  - Junjian Zhang; Chun-Guang Li; Chong You; Xianbiao Qi; Honggang Zhang; Jun Guo; Zhouchen Lin. *CVPR 2019*\n- Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation.\n  - Xin Wang; Qiuyuan Huang; Asli Celikyilmaz; Jianfeng Gao; Dinghan Shen; Yuan-Fang Wang; William Yang Wang; Lei Zhang. *CVPR 2019*\n- Unsupervised 3D Pose Estimation With Geometric Self-Supervision.\n  - Ching-Hang Chen; Ambrish Tyagi; Amit Agrawal; Dylan Drover; Rohith MV; Stefan Stojanov; James M. Rehg. *CVPR 2019*\n- Learning to Generate Grounded Image Captions without Localization Supervision. [[pdf]](https://arxiv.org/pdf/1906.00283.pdf)\n  - Chih-Yao Ma; Yannis Kalantidis; Ghassan AlRegib; Peter Vajda; Marcus Rohrbach; Zsolt Kira.\n- VideoBERT: A Joint Model for Video and Language Representation Learning [[pdf]](https://arxiv.org/pdf/1904.01766.pdf)\n  - Chen Sun, Austin Myers, Carl Vondrick, Kevin Murphy, Cordelia Schmid. *ICCV 2019*\n- S4L: Self-Supervised Semi-Supervised Learning\n  [[pdf]](https://arxiv.org/pdf/1905.03670.pdf)\n  - Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, Lucas Beyer\n- Countering Noisy Labels By Learning From Auxiliary Clean Labels [[pdf]]( https://arxiv.org/pdf/1905.13305.pdf )\n  - Tsung Wei Tsai, Chongxuan Li, Jun Zhu\n\n## Machine Learning\n-   Self-taught Learning: Transfer Learning from Unlabeled Data.\n    [[pdf]](https://ai.stanford.edu/~hllee/icml07-selftaughtlearning.pdf)\n    -   Raina, Rajat and Battle, Alexis and Lee, Honglak and Packer,\n        Benjamin and Ng, Andrew Y. *ICML 2007*\n\n-   Representation Learning: A Review and New Perspectives.\n    [[pdf]](https://arxiv.org/pdf/1206.5538.pdf)\n    -   Bengio, Yoshua and Courville, Aaron and Vincent, Pascal. *TPAMI 2013*.\n\n### Reinforcement Learning\n- Curiosity-driven Exploration by Self-supervised Prediction. \n  [[pdf]](http://pathak22.github.io/noreward-rl/resources/icml17.pdf) \n  [[code]](https://pathak22.github.io/noreward-rl/index.html#sourceCode)\n  - Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, and Trevor Darrell. *ICML 2017*\n\n- Large-Scale Study of Curiosity-Driven Learning.\n  [[pdf]](https://pathak22.github.io/large-scale-curiosity/resources/largeScaleCuriosity2018.pdf) \n  - Yuri Burda*, Harri Edwards*, Deepak Pathak*, Amos Storkey, Trevor Darrell and Alexei A. Efros\n\n- Playing hard exploration games by watching YouTube.\n  [[pdf]](https://papers.nips.cc/paper/7557-playing-hard-exploration-games-by-watching-youtube.pdf) \n  - Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas. *NIPS 2018*\n  \n- Unsupervised State Representation Learning in Atari.\n  [[pdf]](https://arxiv.org/pdf/1906.08226.pdf)\n  [[code]](https://github.com/mila-iqia/atari-representation-learning)\n  - Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R Devon Hjelm. *NeurIPS 2019*\n\n\n## Robotics\n\n### 2006\n- Improving Robot Navigation Through Self-Supervised Online Learning\n  [[pdf]](http://www.roboticsproceedings.org/rss02/p04.pdf)\n  - Boris Sofman, Ellie Lin, J. Andrew Bagnell, Nicolas Vandapel, and Anthony Stentz\n  \n- Reverse Optical Flow for Self-Supervised Adaptive Autonomous Robot Navigation\n  [[pdf]](https://www.cs.ait.ac.th/~mdailey/cvreadings/Lookingbill-ReverseOptical.pdf)\n  - A. Lookingbill, D. Lieb, J. Rogers and J. Curry\n\n### 2009\n- Learning Long-Range Vision for Autonomous Off-Road Driving\n  [[pdf]](http://yann.lecun.com/exdb/publis/pdf/hadsell-jfr-09.pdf)\n  - Raia Hadsell, Pierre Sermanet, Jan Ben, Ayse Erkan, Marco Scoffier, Koray Kavukcuoglu, Urs Muller, Yann LeCun\n\n### 2012\n- Self-supervised terrain classification for planetary surface exploration rovers\n  [[pdf]](https://pdfs.semanticscholar.org/66b7/eef326d1db1fa2b19d5dc6b84d3d2a95b76c.pdf)\n  - Christopher A. Brooks, Karl Iagnemma \n  \n### 2014\n- Terrain Traversability Analysis Using Multi-Sensor Data Correlation by a Mobile Robot\n  [[pdf]](http://sensor.eng.shizuoka.ac.jp/pdf/2014/SII.pdf)\n  - Mohammed Abdessamad Bekhti, Yuichi Kobayashi and Kazuki Matsumura\n  \n### 2015\n- Online self-supervised learning for dynamic object segmentation\n  [[pdf]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.875.5829\u0026rep=rep1\u0026type=pdf)\n  - Vitor Guizilini and Fabio Ramos, The International Journal of Robotics Research\n\n- Self-Supervised Online Learning of Basic Object Push Affordances\n  [[pdf]](http://abr.ijs.si/pdf/1429861734-RidgeIJARS2015.pdf)\n  - Barry Ridge, Ales Leonardis, Ales Ude, Miha Denisa, and Danijel Skocaj\n  \n- Self-supervised learning of grasp dependent tool affordances on the iCub Humanoid robot\n  [[pdf]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\u0026arnumber=7139640)\n  - Tanis Mar, Vadim Tikhanoff, Giorgio Metta, and Lorenzo Natale\n\n### 2016\n- Persistent self-supervised learning principle: from stereo to monocular vision for obstacle avoidance\n  [[pdf]](https://arxiv.org/pdf/1603.08047.pdf)\n  - Kevin van Hecke, Guido de Croon, Laurens van der Maaten, Daniel Hennes, and Dario Izzo\n\n- The Curious Robot: Learning Visual Representations via Physical Interactions. \n  [[pdf]](https://arxiv.org/pdf/1604.01360v2)\n  - Lerrel Pinto and Dhiraj Gandhi and Yuanfeng Han and Yong-Lae Park and Abhinav Gupta. *ECCV 2016*\n\n-   Learning to Poke by Poking: Experiential Learning of Intuitive Physics.\n    [\\[pdf\\]](https://arxiv.org/abs/1606.07419)\n    -   Agrawal, Pulkit and Nair, Ashvin V and Abbeel, Pieter and Malik, Jitendra and Levine, Sergey. *NIPS 2016*\n\n-   Supersizing Self-supervision: Learning to Grasp from 50K Tries and\n    700 Robot Hours. [\\[pdf\\]](https://arxiv.org/pdf/1509.06825.pdf)\n    -   Pinto, Lerrel and Gupta, Abhinav. *ICRA 2016*\n    \n### 2017\n-  Supervision via Competition: Robot Adversaries for Learning Tasks.\n   [[pdf]](https://arxiv.org/pdf/1610.01685.pdf)\n   - Pinto, Lerrel and Davidson, James and Gupta, Abhinav. *ICRA 2017*\n\n- Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge.\n  [[pdf]](https://arxiv.org/pdf/1803.09956.pdf) \n  [[Project]](http://apc.cs.princeton.edu/)\n  - Andy Zeng, Kuan-Ting Yu, Shuran Song, Daniel Suo, Ed Walker Jr., Alberto Rodriguez, Jianxiong Xiao. *ICRA 2017* \n\n- Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation.\n  [[pdf]](https://arxiv.org/abs/1703.02018) \n  [[Project]](https://ropemanipulation.github.io/)\n  - Ashvin Nair*, Dian Chen*, Pulkit Agrawal*, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine. *ICRA 2017*\n\n- Learning to Fly by Crashing\n  [[pdf]](https://arxiv.org/abs/1704.05588)\n  - Dhiraj Gandhi, Lerrel Pinto, Abhinav Gupta *IROS 2017*\n  \n- Self-supervised learning as an enabling technology for future space exploration robots: ISS experiments on monocular distance learning\n  [[pdf]](http://www.esa.int/gsp/ACT/doc/AI/pub/ACT-RPR-AI-2017-ACTA-SSL.pdf)\n  - K. van Hecke, G. C. de Croon, D. Hennes, T. P. Setterfield, A. Saenz- Otero, and D. Izzo\n\n- Unsupervised Perceptual Rewards for Imitation Learning.\n  [[pdf]](https://arxiv.org/abs/1612.06699)\n  [[project]](https://sermanet.github.io/rewards/)\n  - Sermanet, Pierre and Xu, Kelvin and Levine, Sergey. *RSS 2017*\n\n- Self-Supervised Visual Planning with Temporal Skip Connections.\n  [[pdf]](http://arxiv.org/pdf/1710.05268)\n  - Frederik Ebert, Chelsea Finn, Alex X. Lee, Sergey Levine. *CoRL2017*\n\n### 2018\n- CASSL: Curriculum Accelerated Self-Supervised Learning. \n  [[pdf]](https://arxiv.org/pdf/1708.01354.pdf) \n  - Adithyavairavan Murali, Lerrel Pinto, Dhiraj Gandhi, Abhinav Gupta. *ICRA 2018*\n\n- Time-Contrastive Networks: Self-Supervised Learning from Video. \n  [[pdf]](https://arxiv.org/pdf/1609.09475.pdf) \n  [[Project]](https://sermanet.github.io/imitate/)\n  - Pierre Sermanet and Corey Lynch and Yevgen Chebotar and Jasmine Hsu and Eric Jang and Stefan Schaal and Sergey Levine. *ICRA 2018*\n\n- Self-Supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation. \n  [[pdf]](http://arxiv.org/pdf/1709.10489) \n  - Gregory Kahn, Adam Villaflor, Bosen Ding, Pieter Abbeel, Sergey Levine. *ICRA 2018*\n\n- Learning Actionable Representations from Visual Observations. \n  [[pdf]](https://arxiv.org/pdf/1609.09475.pdf) \n  [[Project]](https://sermanet.github.io/imitate/)\n  - Dwibedi, Debidatta and Tompson, Jonathan and Lynch, Corey and Sermanet, Pierre. *IROS 2018* \n  \n- Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning.\n  [[pdf]](https://arxiv.org/abs/1808.00928) \n  [[Project]](https://sites.google.com/view/actionablerepresentations/)\n  - Andy Zeng, Shuran Song, Stefan Welker, Johnny Lee, Alberto Rodriguez, Thomas Funkhouser. *IROS 2018* \n  \n- Visual Reinforcement Learning with Imagined Goals.\n  [[pdf]](https://arxiv.org/abs/1807.04742) \n  [[Project]](https://sites.google.com/site/visualrlwithimaginedgoals/)\n  - Ashvin Nair*, Vitchyr Pong*, Murtaza Dalal, Shikhar Bahl, Steven Lin, Sergey Levine.*NeurIPS 2018*\n\n- Grasp2Vec: Learning Object Representations from Self-Supervised Grasping.\n  [[pdf]](https://arxiv.org/pdf/1811.06964.pdf) \n  [[Project]](https://sites.google.com/site/grasp2vec/home)\n  - Eric Jang*, Coline Devin*, Vincent Vanhoucke, Sergey Levine. *CoRL 2018*\n\n- Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning.\n  [[pdf]](https://arxiv.org/pdf/1810.03043.pdf) \n  [[Project]](https://sites.google.com/view/robustness-via-retrying)\n  - Frederik Ebert, Sudeep Dasari, Alex X. Lee, Sergey Levine, Chelsea Finn. *CoRL 2018*\n\n### 2019\n- Learning Long-Range Perception Using Self-Supervision from Short-Range Sensors and Odometry.\n  [[pdf]](https://arxiv.org/abs/1809.07207)\n  - Mirko Nava, Jerome Guzzi, R. Omar Chavez-Garcia, Luca M. Gambardella, Alessandro Giusti. *Robotics and Automation Letters*\n\n- Learning Latent Plans from Play. \n  [[pdf]](https://arxiv.org/pdf/1903.01973.pdf) \n  [[Project]](https://learning-from-play.github.io/)\n  - COREY LYNCH, MOHI KHANSARI, TED XIAO, VIKASH KUMAR, JONATHAN TOMPSON, SERGEY LEVINE, PIERRE SERMANET\n\n\n## NLP\n- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.\n  [[pdf]](https://arxiv.org/abs/1810.04805)\n  [[link]](https://github.com/google-research/bert)\n  - Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. *NAACL 2019 Best Long Paper*\n\n- Self-Supervised Dialogue Learning\n  [[pdf]](https://arxiv.org/pdf/1907.00448.pdf)\n  - Jiawei Wu, Xin Wang, William Yang Wang. *ACL 2019*\n\n- Self-Supervised Learning for Contextualized Extractive Summarization\n  [[pdf]](https://arxiv.org/pdf/1906.04466.pdf)\n  - Hong Wang, Xin Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, William Yang Wang. *ACL 2019*\n  \n## Talks\n- The power of Self-Learning Systems. Demis Hassabis (DeepMind).\n  [[link]](https://youtu.be/wxis9FrCHbw)\n- Supersizing Self-Supervision: Learning Perception and Action without Human Supervision. Abhinav Gupta (CMU).\n  [[link]](https://simons.berkeley.edu/talks/abhinav-gupta-2017-3-28)\n- Self-supervision, Meta-supervision, Curiosity: Making Computers Study Harder. Alyosha Efros (UCB) \n  [[link]](https://business.facebook.com/academics/videos/1632981350086599)\n- Unsupervised Visual Learning Tutorial. *CVPR 2018* \n  [[part 1]](https://www.youtube.com/watch?v=gSqmUOAMwcc) \n  [[part 2]](https://www.youtube.com/watch?v=BijK_US6A0w)\n- Self-Supervised Learning. Andrew Zisserman (Oxford \u0026 Deepmind). \n  [[pdf]](https://project.inria.fr/paiss/files/2018/07/zisserman-self-supervised.pdf)\n- Graph Embeddings, Content Understanding, \u0026 Self-Supervised Learning. Yann LeCun. (NYU \u0026 FAIR)\n  [[pdf]](https://drive.google.com/file/d/12pDCno02FJPDEBk4iGuuaj8b2rr48Hh0/view)\n  [[video]](https://www.youtube.com/watch?v=UGPT64wo7lU)\n- Self-supervised learning: could machines learn like humans? Yann LeCun @EPFL. \n  [[video]](https://www.youtube.com/watch?v=7I0Qt7GALVk)\n- Week 9 (b): CS294-158 Deep Unsupervised Learning(Spring 2019). Alyosha Efros @UC Berkeley. \n  [[video]](https://www.youtube.com/watch?v=PX11C5Vfo9U)\n\n## Thesis\n- Supervision Beyond Manual Annotations for Learning Visual Representations. Carl Doersch. [[pdf]](http://www.carldoersch.com/docs/thesis.pdf).\n- Image Synthesis for Self-Supervised Visual Representation Learning. Richard Zhang. [[pdf]](https://www2.eecs.berkeley.edu/Pubs/TechRpts/2018/EECS-2018-36.pdf).\n- Visual Learning beyond Direct Supervision. Tinghui Zhou. [[pdf]](https://www2.eecs.berkeley.edu/Pubs/TechRpts/2018/EECS-2018-128.pdf).\n- Visual Learning with Minimal Human Supervision. Ishan Misra. [[pdf]](https://www.ri.cmu.edu/publications/visual-learning-with-minimal-human-supervision/).\n\n## Blog\n- Self-Supervised Representation Learning. Lilian Weng. [[link]](https://lilianweng.github.io/lil-log/2019/11/10/self-supervised-learning.html).\n\n## License\nTo the extent possible under law, [Zhongzheng Ren](https://jason718.github.io/) has waived all copyright and related or neighboring rights to this work.\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/eric-erki%2Fawesome-self-supervised-learning/projects"}