100+篇《自监督学习(Self-Supervised Learning)》论文最新合集

2020 年 3 月 18 日 专知
100+篇《自监督学习(Self-Supervised Learning)》论文最新合集

自监督学习(Self-Supervised Learning)是一种介于无监督和监督学习之间的一种新范式,旨在减少对大量带注释数据的挑战性需求。它通过定义无注释(annotation-free)的前置任务(pretext task),为特征学习提供代理监督信号。jason718整理了关于自监督学习最新的论文合集,非常值得查看!


地址:

https://github.com/jason718/awesome-self-supervised-learning

Table of Contents

  • Computer Vision (CV)

    • Survey

    • Image Representation Learning

    • Video Representation Learning

    • Geometry

    • Audio

    • Others

  • Machine Learning

    • Reinforcement Learning

  • Robotics

  • Natural Language Processing (NLP)

  • Automatic Speech Recognition (ASR)

  • Talks

  • Thesis

  • Blog

Computer Vision

Survey

  • Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey[pdf]

    • Longlong Jing and Yingli Tian.

Image Representation Learning

Benchmark code

FAIR Self-Supervision Benchmark [repo]: various benchmark (and legacy) tasks for evaluating quality of visual representations learned by various self-supervision approaches.

2015

  • Unsupervised Visual Representation Learning by Context Prediction[pdf] [code]

    • Doersch, Carl and Gupta, Abhinav and Efros, Alexei A. ICCV 2015

  • 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

  • Learning image representations tied to ego-motion[pdf] [code]

    • Jayaraman, Dinesh and Grauman, Kristen. ICCV 2015

2016

  • 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

  • Slow and steady feature analysis: higher order temporal coherence in video. [pdf]

    • Jayaraman, Dinesh and Grauman, Kristen. CVPR 2016

  • 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

  • Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles. [pdf] [code]

    • Noroozi, Mehdi and Favaro, Paolo. ECCV 2016

  • 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

  • Learning Representations for Automatic Colorization. [pdf] [code]

    • Larsson, Gustav and Maire, Michael and Shakhnarovich, Gregory. ECCV 2016

  • 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

2017

  • 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

  • Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. [pdf] [code]

    • Zhang, Richard and Isola, Phillip and Efros, Alexei A. CVPR 2017

  • Learning Features by Watching Objects Move. [pdf] [code]

    • Pathak, Deepak and Girshick, Ross and Dollar, Piotr and Darrell, Trevor and Hariharan, Bharath. CVPR 2017

  • Colorization as a Proxy Task for Visual Understanding. [pdf] [code]

    • Larsson, Gustav and Maire, Michael and Shakhnarovich, Gregory. CVPR 2017

  • 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

  • Representation Learning by Learning to Count. [pdf]

    • Noroozi, Mehdi and Pirsiavash, Hamed and Favaro, Paolo. ICCV 2017

  • 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

2018

  • Unsupervised Feature Learning via Non-parameteric Instance Discrimination [pdf] [code]

    • Zhirong Wu, Yuanjun Xiong and X Yu Stella and Dahua Lin. CVPR 2018

  • Learning Image Representations by Completing Damaged Jigsaw Puzzles. [pdf]

    • Kim, Dahun and Cho, Donghyeon and Yoo, Donggeun and Kweon, In So. WACV 2018

  • Unsupervised Representation Learning by Predicting Image Rotations. [pdf] [code]

    • Spyros Gidaris and Praveer Singh and Nikos Komodakis. ICLR 2018

  • 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

  • Improvements to context based self-supervised learning. [pdf]

    • Terrell Mundhenk and Daniel Ho and Barry Chen. CVPR 2018

  • Self-Supervised Feature Learning by Learning to Spot Artifacts. [pdf] [code]

    • Simon Jenni and Universität Bern and Paolo Favaro. CVPR 2018

  • Boosting Self-Supervised Learning via Knowledge Transfer. [pdf]

    • Mehdi Noroozi and Ananth Vinjimoor and Paolo Favaro and Hamed Pirsiavash. CVPR 2018

  • Cross-domain Self-supervised Multi-task Feature Learning Using Synthetic Imagery. [pdf] [code]

    • Zhongzheng Ren and Yong Jae Lee. CVPR 2018

  • 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

  • Deep Clustering for Unsupervised Learning of Visual Features [pdf]

    • Mathilde Caron, Piotr Bojanowski, Armand Joulin, Matthijs Douze. ECCV 2018

  • Cross Pixel Optical-Flow Similarity for Self-Supervised Learning. [pdf]

    • Aravindh Mahendran, James Thewlis, Andrea Vedaldi. ACCV 2018

2019

  • Representation Learning with Contrastive Predictive Coding. [pdf]

    • Aaron van den Oord, Yazhe Li, Oriol Vinyals.

  • Self-Supervised Learning via Conditional Motion Propagation. [pdf] [code]

    • Xiaohang Zhan, Xingang Pan, Ziwei Liu, Dahua Lin, and Chen Change Loy. CVPR 2019

  • 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

  • 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.

  • Learning Representations by Maximizing Mutual Information Across Views. [pdf] [code]

    • Philip Bachman, R Devon Hjelm, William Buchwalter

  • Selfie: Self-supervised Pretraining for Image Embedding. [pdf]

    • Trieu H. Trinh, Minh-Thang Luong, Quoc V. Le

  • 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

  • Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty [pdf] [code]

    • Dan Hendrycks, Mantas Mazeika, Saurav Kadavath, Dawn Song. NeurIPS 2019

  • Boosting Few-Shot Visual Learning with Self-Supervision [pdf]

    • pyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, and Matthieu Cord. ICCV 2019

  • Self-Supervised Generalisation with Meta Auxiliary Learning [pdf] [code]

    • Shikun Liu, Andrew J. Davison, Edward Johns. NeurIPS 2019

  • Wasserstein Dependency Measure for Representation Learning [pdf] [code]

    • Sherjil Ozair, Corey Lynch, Yoshua Bengio, Aaron van den Oord, Sergey Levine, Pierre Sermanet. NeurIPS 2019

  • Scaling and Benchmarking Self-Supervised Visual Representation Learning [pdf] [code]

    • Priya Goyal, Dhruv Mahajan, Abhinav Gupta, Ishan Misra. ICCV 2019

2020

  • 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

  • On Mutual Information Maximization for Representation Learning [pdf] [code]

    • Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic. ICLR 2020

  • Understanding the Limitations of Variational Mutual Information Estimators [pdf] [code]

    • Jiaming Song, Stefano Ermon. ICLR 2020

  • Automatic Shortcut Removal for Self-Supervised Representation Learning [pdf]

    • Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen

  • Momentum Contrast for Unsupervised Visual Representation Learning [pdf]

    • Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, Ross Girshick. FAIR

  • A Simple Framework for Contrastive Learning of Visual Representations [pdf]

    • Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey Hinton

  • ClusterFit: Improving Generalization of Visual Representations [pdf]

    • Xueting Yan*, Ishan Misra*, Abhinav Gupta, Deepti Ghadiyaram**, Dhruv Mahajan**. CVPR 2020

  • Self-Supervised Learning of Pretext-Invariant Representations [pdf]

    • Ishan Misra, Laurens van der Maaten. CVPR 2020

Video Representation Learning

  • Unsupervised Learning of Video Representations using LSTMs. [pdf] [code]

    • Srivastava, Nitish and Mansimov, Elman and Salakhudinov, Ruslan. ICML 2015

  • Shuffle and Learn: Unsupervised Learning using Temporal Order Verification. [pdf] [code]

    • Ishan Misra, C. Lawrence Zitnick and Martial Hebert. ECCV 2016

  • LSTM Self-Supervision for Detailed Behavior Analysis [pdf]

    • Biagio Brattoli*, Uta Büchler*, Anna-Sophia Wahl, Martin E. Schwab, and Björn Ommer. CVPR 2017

  • Self-Supervised Video Representation Learning With Odd-One-Out Networks. [pdf]

    • Basura Fernando and Hakan Bilen and Efstratios Gavves and Stephen Gould. CVPR 2017

  • 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

  • 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

  • Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning. [pdf]

    • Biagio Brattoli*, Uta Büchler*, and Björn Ommer. ECCV 2018

  • Self-supervised learning of a facial attribute embedding from video. [pdf]

    • Wiles, O., Koepke, A.S., Zisserman, A. BMVC 2018

  • 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

  • DynamoNet: Dynamic Action and Motion Network. [pdf]

    • Ali Diba; Vivek Sharma, Luc Van Gool, Rainer Stiefelhagen. ICCV 2019

  • Learning Correspondence from the Cycle-consistency of Time. [pdf] [code]

    • Xiaolong Wang*, Allan Jabri* and Alexei A. Efros. CVPR 2019

  • 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

Geometry

  • Self-supervised Learning of Motion Capture. [pdf] [code] [web]

    • Tung, Hsiao-Yu and Tung, Hsiao-Wei and Yumer, Ersin and Fragkiadaki, Katerina. NIPS 2017

  • Unsupervised Learning of Depth and Ego-Motion from Video. [pdf] [code] [web]

    • Zhou, Tinghui and Brown, Matthew and Snavely, Noah and Lowe, David G. CVPR 2017

  • Active Stereo Net: End-to-End Self-Supervised Learning for Active Stereo Systems. [project]

    • Yinda Zhang*, Sean Fanello, Sameh Khamis, Christoph Rhemann, Julien Valentin, Adarsh Kowdle, Vladimir Tankovich, Shahram Izadi, Thomas Funkhouser. ECCV 2018

  • Self-Supervised Relative Depth Learning for Urban Scene Understanding. [pdf] [project]

    • Huaizu Jiang*, Erik Learned-Miller, Gustav Larsson, Michael Maire, Greg Shakhnarovich. ECCV 2018

  • Geometry-Aware Learning of Maps for Camera Localization. [pdf] [code]

    • Samarth Brahmbhatt, Jinwei Gu, Kihwan Kim, James Hays, and Jan Kautz. CVPR 2018

  • Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection. [pdf] [web]

    • David Novotny, Samuel Albanie, Diane Larlus, Andrea Vedaldi. CVPR 2018

  • Self-Supervised Learning of 3D Human Pose Using Multi-View Geometry. [pdf]

    • Muhammed Kocabas; Salih Karagoz; Emre Akbas. CVPR 2019

  • SelFlow: Self-Supervised Learning of Optical Flow. [pdf]

    • Jiangliu Wang; Jianbo Jiao; Linchao Bao; Shengfeng He; Yunhui Liu; Wei Liu. CVPR 2019

  • Unsupervised Learning of Landmarks by Descriptor Vector Exchange. [pdf] [code] [web]

    • James Thewlis, Samuel Albanie, Hakan Bilen, Andrea Vedaldi. ICCV 2019

Audio

  • Audio-Visual Scene Analysis with Self-Supervised Multisensory Features. [pdf] [code]

    • Andrew Owens, Alexei A. Efros. ECCV 2018

  • Objects that Sound. [pdf]

    • R. Arandjelović, A. Zisserman. ECCV 2018

  • Learning to Separate Object Sounds by Watching Unlabeled Video. [pdf] [project]

    • Ruohan Gao, Rogerio Feris, Kristen Grauman. ECCV 2018

  • The Sound of Pixels. [pdf] [project]

    • Zhao, Hang and Gan, Chuang and Rouditchenko, Andrew and Vondrick, Carl and McDermott, Josh and Torralba, Antonio. ECCV 2018

  • Learnable PINs: Cross-Modal Embeddings for Person Identity. [pdf] [web]

    • Arsha Nagrani, Samuel Albanie, Andrew Zisserman. ECCV 2018

  • Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization. [pdf]

    • Bruno Korbar,Dartmouth College, Du Tran, Lorenzo Torresani. NIPS 2018

  • Self-Supervised Generation of Spatial Audio for 360° Video. [pdf]

    • Pedro Morgado, Nuno Nvasconcelos, Timothy Langlois, Oliver Wang. NIPS 2018

  • TriCycle: Audio Representation Learning from Sensor Network Data Using Self-Supervision [pdf]

    • Mark Cartwright, Jason Cramer, Justin Salamon, Juan Pablo Bello. WASPAA 2019

Others

  • Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model. [pdf]

    • Qixiang Ye, Tianliang Zhang, Qiang Qiu, Baochang Zhang, Jie Chen, Guillermo Sapiro. CVPR 2017

  • Free Supervision from Video Games. [pdf] [project+code]

    • Philipp Krähenbühl. CVPR 2018

  • Fighting Fake News: Image Splice Detection via Learned Self-Consistency [pdf] [code]

    • Minyoung Huh*, Andrew Liu*, Andrew Owens, Alexei A. Efros. ECCV 2018

  • Self-supervised Tracking by Colorization (Tracking Emerges by Colorizing Videos). [pdf]

    • Carl Vondrick*, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama, Kevin Murphy. ECCV 2018

  • High-Fidelity Image Generation With Fewer Labels. [pdf]

    • Mario Lucic*, Michael Tschannen*, Marvin Ritter*, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly.

  • Self-supervised Fitting of Articulated Meshes to Point Clouds.

    • Chun-Liang Li, Tomas Simon, Jason Saragih, Barnabás Póczos and Yaser Sheikh. CVPR 2019

  • SCOPS: Self-Supervised Co-Part Segmentation.

    • Wei-Chih Hung, Varun Jampani, Sifei Liu, Pavlo Molchanov, Ming-Hsuan Yang, and Jan Kautz. CVPR 2019

  • Self-Supervised GANs via Auxiliary Rotation Loss.

    • Ting Chen; Xiaohua Zhai; Marvin Ritter; Mario Lucic; Neil Houlsby. CVPR 2019

  • Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking.

    • Jae Shin Yoon; Takaaki Shiratori; Shoou-I Yu; Hyun Soo Park. CVPR 2019

  • Multi-Task Self-Supervised Object Detection via Recycling of Bounding Box Annotations.

    • Wonhee Lee; Joonil Na; Gunhee Kim. CVPR 2019

  • Self-Supervised Convolutional Subspace Clustering Network.

    • Junjian Zhang; Chun-Guang Li; Chong You; Xianbiao Qi; Honggang Zhang; Jun Guo; Zhouchen Lin. CVPR 2019

  • Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation.

    • Xin Wang; Qiuyuan Huang; Asli Celikyilmaz; Jianfeng Gao; Dinghan Shen; Yuan-Fang Wang; William Yang Wang; Lei Zhang. CVPR 2019

  • Unsupervised 3D Pose Estimation With Geometric Self-Supervision.

    • Ching-Hang Chen; Ambrish Tyagi; Amit Agrawal; Dylan Drover; Rohith MV; Stefan Stojanov; James M. Rehg. CVPR 2019

  • Learning to Generate Grounded Image Captions without Localization Supervision. [pdf]

    • Chih-Yao Ma; Yannis Kalantidis; Ghassan AlRegib; Peter Vajda; Marcus Rohrbach; Zsolt Kira.

  • VideoBERT: A Joint Model for Video and Language Representation Learning [pdf]

    • Chen Sun, Austin Myers, Carl Vondrick, Kevin Murphy, Cordelia Schmid. ICCV 2019

  • S4L: Self-Supervised Semi-Supervised Learning [pdf]

    • Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, Lucas Beyer

  • Countering Noisy Labels By Learning From Auxiliary Clean Labels [pdf]

    • Tsung Wei Tsai, Chongxuan Li, Jun Zhu

Machine Learning

  • Self-taught Learning: Transfer Learning from Unlabeled Data. [pdf]

    • Raina, Rajat and Battle, Alexis and Lee, Honglak and Packer, Benjamin and Ng, Andrew Y. ICML 2007

  • Representation Learning: A Review and New Perspectives. [pdf]

    • Bengio, Yoshua and Courville, Aaron and Vincent, Pascal. TPAMI 2013.

Reinforcement Learning

  • Curiosity-driven Exploration by Self-supervised Prediction. [pdf] [code]

    • Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, and Trevor Darrell. ICML 2017

  • Large-Scale Study of Curiosity-Driven Learning. [pdf]

    • Yuri Burda*, Harri Edwards*, Deepak Pathak*, Amos Storkey, Trevor Darrell and Alexei A. Efros

  • Playing hard exploration games by watching YouTube. [pdf]

    • Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas. NIPS 2018

  • Unsupervised State Representation Learning in Atari. [pdf] [code]

    • Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R Devon Hjelm. NeurIPS 2019

Robotics

2006

  • Improving Robot Navigation Through Self-Supervised Online Learning [pdf]

    • Boris Sofman, Ellie Lin, J. Andrew Bagnell, Nicolas Vandapel, and Anthony Stentz

  • Reverse Optical Flow for Self-Supervised Adaptive Autonomous Robot Navigation [pdf]

    • A. Lookingbill, D. Lieb, J. Rogers and J. Curry

2009

  • Learning Long-Range Vision for Autonomous Off-Road Driving [pdf]

    • Raia Hadsell, Pierre Sermanet, Jan Ben, Ayse Erkan, Marco Scoffier, Koray Kavukcuoglu, Urs Muller, Yann LeCun

2012

  • Self-supervised terrain classification for planetary surface exploration rovers [pdf]

    • Christopher A. Brooks, Karl Iagnemma

2014

  • Terrain Traversability Analysis Using Multi-Sensor Data Correlation by a Mobile Robot [pdf]

    • Mohammed Abdessamad Bekhti, Yuichi Kobayashi and Kazuki Matsumura

2015

  • Online self-supervised learning for dynamic object segmentation [pdf]

    • Vitor Guizilini and Fabio Ramos, The International Journal of Robotics Research

  • Self-Supervised Online Learning of Basic Object Push Affordances [pdf]

    • Barry Ridge, Ales Leonardis, Ales Ude, Miha Denisa, and Danijel Skocaj

  • Self-supervised learning of grasp dependent tool affordances on the iCub Humanoid robot [pdf]

    • Tanis Mar, Vadim Tikhanoff, Giorgio Metta, and Lorenzo Natale

2016

  • Persistent self-supervised learning principle: from stereo to monocular vision for obstacle avoidance [pdf]

    • Kevin van Hecke, Guido de Croon, Laurens van der Maaten, Daniel Hennes, and Dario Izzo

  • The Curious Robot: Learning Visual Representations via Physical Interactions. [pdf]

    • Lerrel Pinto and Dhiraj Gandhi and Yuanfeng Han and Yong-Lae Park and Abhinav Gupta. ECCV 2016

  • Learning to Poke by Poking: Experiential Learning of Intuitive Physics. [pdf]

    • Agrawal, Pulkit and Nair, Ashvin V and Abbeel, Pieter and Malik, Jitendra and Levine, Sergey. NIPS 2016

  • Supersizing Self-supervision: Learning to Grasp from 50K Tries and 700 Robot Hours. [pdf]

    • Pinto, Lerrel and Gupta, Abhinav. ICRA 2016

2017

  • Supervision via Competition: Robot Adversaries for Learning Tasks. [pdf]

    • Pinto, Lerrel and Davidson, James and Gupta, Abhinav. ICRA 2017

  • Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge. [pdf] [Project]

    • Andy Zeng, Kuan-Ting Yu, Shuran Song, Daniel Suo, Ed Walker Jr., Alberto Rodriguez, Jianxiong Xiao. ICRA 2017

  • Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation. [pdf] [Project]

    • Ashvin Nair*, Dian Chen*, Pulkit Agrawal*, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine. ICRA 2017

  • Learning to Fly by Crashing [pdf]

    • Dhiraj Gandhi, Lerrel Pinto, Abhinav Gupta IROS 2017

  • Self-supervised learning as an enabling technology for future space exploration robots: ISS experiments on monocular distance learning [pdf]

    • K. van Hecke, G. C. de Croon, D. Hennes, T. P. Setterfield, A. Saenz- Otero, and D. Izzo

  • Unsupervised Perceptual Rewards for Imitation Learning. [pdf] [project]

    • Sermanet, Pierre and Xu, Kelvin and Levine, Sergey. RSS 2017

  • Self-Supervised Visual Planning with Temporal Skip Connections. [pdf]

    • Frederik Ebert, Chelsea Finn, Alex X. Lee, Sergey Levine. CoRL2017

2018

  • CASSL: Curriculum Accelerated Self-Supervised Learning. [pdf]

    • Adithyavairavan Murali, Lerrel Pinto, Dhiraj Gandhi, Abhinav Gupta. ICRA 2018

  • Time-Contrastive Networks: Self-Supervised Learning from Video. [pdf] [Project]

    • Pierre Sermanet and Corey Lynch and Yevgen Chebotar and Jasmine Hsu and Eric Jang and Stefan Schaal and Sergey Levine. ICRA 2018

  • Self-Supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation. [pdf]

    • Gregory Kahn, Adam Villaflor, Bosen Ding, Pieter Abbeel, Sergey Levine. ICRA 2018

  • Learning Actionable Representations from Visual Observations. [pdf] [Project]

    • Dwibedi, Debidatta and Tompson, Jonathan and Lynch, Corey and Sermanet, Pierre. IROS 2018

  • Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning. [pdf] [Project]

    • Andy Zeng, Shuran Song, Stefan Welker, Johnny Lee, Alberto Rodriguez, Thomas Funkhouser. IROS 2018

  • Visual Reinforcement Learning with Imagined Goals. [pdf] [Project]

    • Ashvin Nair*, Vitchyr Pong*, Murtaza Dalal, Shikhar Bahl, Steven Lin, Sergey Levine.NeurIPS 2018

  • Grasp2Vec: Learning Object Representations from Self-Supervised Grasping. [pdf] [Project]

    • Eric Jang*, Coline Devin*, Vincent Vanhoucke, Sergey Levine. CoRL 2018

  • Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning. [pdf] [Project]

    • Frederik Ebert, Sudeep Dasari, Alex X. Lee, Sergey Levine, Chelsea Finn. CoRL 2018

2019

  • Learning Long-Range Perception Using Self-Supervision from Short-Range Sensors and Odometry. [pdf]

    • Mirko Nava, Jerome Guzzi, R. Omar Chavez-Garcia, Luca M. Gambardella, Alessandro Giusti. Robotics and Automation Letters

  • Learning Latent Plans from Play. [pdf] [Project]

    • Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, Pierre Sermanet

2020

  • Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video. [pdf] [Project]

    • Oier Mees, Markus Merklinger, Gabriel Kalweit, Wolfram Burgard ICRA 2020

NLP

  • BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. [pdf] [link]

    • Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. NAACL 2019 Best Long Paper

  • Self-Supervised Dialogue Learning [pdf]

    • Jiawei Wu, Xin Wang, William Yang Wang. ACL 2019

  • Self-Supervised Learning for Contextualized Extractive Summarization [pdf]

    • Hong Wang, Xin Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, William Yang Wang. ACL 2019

  • A Mutual Information Maximization Perspective of Language Representation Learning [pdf]

    • Lingpeng Kong, Cyprien de Masson d'Autume, Lei Yu, Wang Ling, Zihang Dai, Dani Yogatama. ICLR 2020

  • VL-BERT: Pre-training of Generic Visual-Linguistic Representations [pdf] [code]

    • Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, Jifeng Dai. ICLR 2020

ASR

  • Learning Robust and Multilingual Speech Representations [pdf]

    • Kazuya Kawakami, Luyu Wang, Chris Dyer, Phil Blunsom, Aaron van den Oord

  • Unsupervised pretraining transfers well across languages [pdf] [code]

    • Morgane Riviere, Armand Joulin, Pierre-Emmanuel Mazare, Emmanuel Dupoux

  • wav2vec: Unsupervised Pre-Training for Speech Recognition [pdf] [code]

    • Steffen Schneider, Alexei Baevski, Ronan Collobert, Michael Auli. INTERSPEECH 2019

  • vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations [pdf]

    • Alexei Baevski, Steffen Schneider, Michael Auli. ICLR 2020

  • Effectiveness of self-supervised pre-training for speech recognition [pdf]

    • Alexei Baevski, Michael Auli, Abdelrahman Mohamed

  • Towards Unsupervised Speech Recognition and Synthesis with Quantized Speech Representation Learning [pdf]

    • Alexander H. Liu, Tao Tu, Hung-yi Lee, Lin-shan Lee

  • Self-Training for End-to-End Speech Recognition [pdf]

    • Jacob Kahn, Ann Lee, Awni Hannun. ICASSP 2020

  • Generative Pre-Training for Speech with Autoregressive Predictive Coding [pdf] [code]

    • Yu-An Chung, James Glass. ICASSP 2020

Talks

  • The power of Self-Learning Systems. Demis Hassabis (DeepMind). [link]

  • Supersizing Self-Supervision: Learning Perception and Action without Human Supervision. Abhinav Gupta (CMU). [link]

  • Self-supervision, Meta-supervision, Curiosity: Making Computers Study Harder. Alyosha Efros (UCB) [link]

  • Unsupervised Visual Learning Tutorial. CVPR 2018 [part 1] [part 2]

  • Self-Supervised Learning. Andrew Zisserman (Oxford & Deepmind). [pdf]

  • Graph Embeddings, Content Understanding, & Self-Supervised Learning. Yann LeCun. (NYU & FAIR) [pdf] [video]

  • Self-supervised learning: could machines learn like humans? Yann LeCun @EPFL. [video]

  • Week 9 (b): CS294-158 Deep Unsupervised Learning(Spring 2019). Alyosha Efros @UC Berkeley. [video]

Thesis

  • Supervision Beyond Manual Annotations for Learning Visual Representations. Carl Doersch. [pdf].

  • Image Synthesis for Self-Supervised Visual Representation Learning. Richard Zhang. [pdf].

  • Visual Learning beyond Direct Supervision. Tinghui Zhou. [pdf].

  • Visual Learning with Minimal Human Supervision. Ishan Misra. [pdf].

Blog

  • Self-Supervised Representation Learning. Lilian Weng. [link].

  • The Illustrated Self-Supervised Learning. Amit Chaudhary. [link]



专知便捷查看

便捷下载,请关注专知公众号(点击上方蓝色专知关注)

  • 后台回复“SSL” 就可以获取100+篇《自监督学习(Self-Supervised Learning)》论文最新合集》专知下载链接

专知,专业可信的人工智能知识分发,让认知协作更快更好!欢迎注册登录专知www.zhuanzhi.ai,获取5000+AI主题干货知识资料!
欢迎微信扫一扫加入专知人工智能知识星球群,获取最新AI专业干货知识教程资料和与专家交流咨询
点击“ 阅读原文 ”,了解使用 专知 ,查看获取5000+AI主题知识资源
登录查看更多
124

相关内容

自监督学习(self-supervised learning)可以被看作是机器学习的一种“理想状态”,模型直接从无标签数据中自行学习,无需标注数据。
专知会员服务
50+阅读 · 2020年3月19日
专知会员服务
106+阅读 · 2020年3月12日
专知会员服务
51+阅读 · 2019年12月22日
Stabilizing Transformers for Reinforcement Learning
专知会员服务
33+阅读 · 2019年10月17日
元学习(Meta Learning)最全论文、视频、书籍资源整理
深度学习与NLP
22+阅读 · 2019年6月20日
强化学习的Unsupervised Meta-Learning
CreateAMind
8+阅读 · 2019年1月7日
Unsupervised Learning via Meta-Learning
CreateAMind
33+阅读 · 2019年1月3日
Zero-Shot Learning相关资源大列表
专知
49+阅读 · 2019年1月1日
大神 一年100篇论文
CreateAMind
14+阅读 · 2018年12月31日
【推荐】SLAM相关资源大列表
机器学习研究会
10+阅读 · 2017年8月18日
A Survey on Bayesian Deep Learning
Arxiv
51+阅读 · 2020年7月2日
Continual Unsupervised Representation Learning
Arxiv
5+阅读 · 2019年10月31日
Arxiv
7+阅读 · 2018年5月23日
小贴士
Top
微信扫码咨询专知VIP会员