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Robotic motor control necessitates the ability to predict the dynamics of environments and interaction objects.
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Neural correlates of visual-motion perception as object-or self-motion
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Deep multi-scale video prediction beyond mean square error
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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End-to-end training of deep visuomotor policies
Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel · 2016
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Attention is all you need
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Learning complex dexterous manipulation with deep reinforcement learning and demonstrations
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Tengda Han, Weidi Xie, and Andrew Zisserman · 2019
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 2019
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Learning dexterous in-hand manipulation
OpenAI: Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, et al · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning
Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, and Karol Hausman · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Rlbench: The robot learning benchmark & learning environment
Stephen James, Zicong Ma, David Rovick Arrojo, and Andrew J Davison · 2020
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Dynamics-aware embeddings
William F Whitney, Rajat Agarwal, Kyunghyun Cho, and Abhinav Gupta · 2020
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Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning
Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, and Sergey Levine · 2020
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robosuite: A modular simulation framework and benchmark for robot learning
Yuke Zhu, Josiah Wong, Ajay Mandlekar, Roberto Martín-Martín, Abhishek Joshi, Soroush Nasiriany, and Yifeng Zhu · 2020
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Beit: Bert pre-training of image transformers
Hangbo Bao, Li Dong, Songhao Piao, and Furu Wei · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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An empirical study of training self-supervised vision transformers. in 2021 ieee
X Chen, S Xie, and K He · 2021
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BC-Z: zero-shot task generalization with robotic imitation learning
Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, and Chelsea Finn · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Trifinger: An open-source robot for learning dexterity
Manuel Wuthrich, Felix Widmaier, Felix Grimminger, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, et al · 2021
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ibot: Image bert pre-training with online tokenizer
Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, and Tao Kong · 2021
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Multimae: Multi-modal multi-task masked autoencoders
Roman Bachmann, David Mizrahi, Andrei Atanov, and Amir Zamir · 2022
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Data2vec: A general framework for self-supervised learning in speech, vision and language
Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, and Michael Auli · 2022
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Human-to-robot imitation in the wild
Shikhar Bahl, Abhinav Gupta, and Deepak Pathak · 2022
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Multimodal masked autoencoders learn transferable representations
Xinyang Geng, Hao Liu, Lisa Lee, Dale Schuurams, Sergey Levine, and Pieter Abbeel · 2022
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Ego4d: Around the world in 3,000 hours of egocentric video
Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, et al · 2022
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Maskvit: Masked visual pre-training for video prediction
Agrim Gupta, Stephen Tian, Yunzhi Zhang, Jiajun Wu, Roberto Martín-Martín, and Li Fei-Fei · 2022
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On pre-training for visuo-motor control: Revisiting a learning-from-scratch baseline
Nicklas Hansen, Zhecheng Yuan, Yanjie Ze, Tongzhou Mu, Aravind Rajeswaran, Hao Su, Huazhe Xu, and Xiaolong Wang · 2022
Cited alongside, same era.
Learning to act from actionless videos through dense correspondences
Po-Chen Ko, Jiayuan Mao, Yilun Du, Shao-Hua Sun, and Joshua B Tenenbaum · 2023
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Understanding masked image modeling via learning occlusion invariant feature
Xiangwen Kong and Xiangyu Zhang · 2023
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Vision-language foundation models as effective robot imitators
Xinghang Li, Minghuan Liu, Hanbo Zhang, Cunjun Yu, Jie Xu, Hongtao Wu, Chilam Cheang, Ya Jing, Weinan Zhang, Huaping Liu, et al · 2023
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Spawnnet: Learning generalizable visuomotor skills from pre-trained networks
Xingyu Lin, John So, Sashwat Mahalingam, Fangchen Liu, and Pieter Abbeel · 2023
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Where are we in the search for an artificial visual cortex for embodied intelligence?
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
Cited alongside, same era.
Egocentric video-language pretraining
Kevin Qinghong Lin, Jinpeng Wang, Mattia Soldan, Michael Wray, Rui Yan, Eric Z XU, Difei Gao, Rong-Cheng Tu, Wenzhe Zhao, Weijie Kong, et al · 2022
Cited alongside, same era.
R3m: A universal visual representation for robot manipulation
Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, and Abhinav Gupta · 2022
Cited alongside, same era.
The unsurprising effectiveness of pre-trained vision models for control
Simone Parisi, Aravind Rajeswaran, Senthil Purushwalkam, and Abhinav Gupta · 2022
Cited alongside, same era.
Dexmv: Imitation learning for dexterous manipulation from human videos
Yuzhe Qin, Yueh-Hua Wu, Shaowei Liu, Hanwen Jiang, Ruihan Yang, Yang Fu, and Xiaolong Wang · 2022
Cited alongside, same era.
Reinforcement learning with action-free pre-training from videos
Younggyo Seo, Kimin Lee, Stephen L James, and Pieter Abbeel · 2022
Cited alongside, same era.
Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training
Zhan Tong, Yibing Song, Jue Wang, and Limin Wang · 2022
Cited alongside, same era.
Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Pieter Abbeel, Jitendra Malik, et al · 2023
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Structured world models from human videos
Russell Mendonca, Shikhar Bahl, and Deepak Pathak · 2023
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EmbodiedGPT: Vision-language pre-training via embodied chain of thought
Yao Mu, Qinglong Zhang, Mengkang Hu, Wenhai Wang, Mingyu Ding, Jun Jin, Bin Wang, Jifeng Dai, Yu Qiao, and Ping Luo · 2023
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Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
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Open x-embodiment: Robotic learning datasets and rt-x models
Abhishek Padalkar, Acorn Pooley, Ajinkya Jain, Alex Bewley, Alex Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anikait Singh, Anthony Brohan, et al · 2023
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Masked world models for visual control
Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, and Pieter Abbeel · 2023
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Lossless adaptation of pretrained vision models for robotic manipulation
Mohit Sharma, Claudio Fantacci, Yuxiang Zhou, Skanda Koppula, Nicolas Heess, Jon Scholz, and Yusuf Aytar · 2023
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Sneha Silwal, Karmesh Yadav, Tingfan Wu, Jay Vakil, Arjun Majumdar, Sergio Arnaud, Claire Chen, Vincent-Pierre Berges, Dhruv Batra, Aravind Rajeswaran, et al · 2023
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Open-world object manipulation using pre-trained vision-language models
Austin Stone, Ted Xiao, Yao Lu, Keerthana Gopalakrishnan, Kuang-Huei Lee, Quan Vuong, Paul Wohlhart, Brianna Zitkovich, Fei Xia, Chelsea Finn, et al · 2023
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Smart: Self-supervised multi-task pretraining with control transformers
Yanchao Sun, Shuang Ma, Ratnesh Madaan, Rogerio Bonatti, Furong Huang, and Ashish Kapoor · 2023
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Octo: An open-source generalist robot policy, 2023
Octo Model Team, Dibya Ghosh, Homer Walke, Karl Pertsch, Kevin Black, Oier Mees, Sudeep Dasari, Joey Hejna, Charles Xu, Jianlan Luo, et al · 2023
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Plex: Making the most of the available data for robotic manipulation pretraining
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, and Andrey Kolobov · 2023
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Bridgedata v2: A dataset for robot learning at scale
Homer Rich Walke, Kevin Black, Tony Z Zhao, Quan Vuong, Chongyi Zheng, Philippe Hansen-Estruch, Andre Wang He, Vivek Myers, Moo Jin Kim, Max Du, et al · 2023
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Any-point trajectory modeling for policy learning
Chuan Wen, Xingyu Lin, John So, Kai Chen, Qi Dou, Yang Gao, and Pieter Abbeel · 2023
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Unleashing large-scale video generative pre-training for visual robot manipulation
Hongtao Wu, Ya Jing, Chilam Cheang, Guangzeng Chen, Jiafeng Xu, Xinghang Li, Minghuan Liu, Hang Li, and Tao Kong · 2023
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Xskill: Cross embodiment skill discovery
Mengda Xu, Zhenjia Xu, Cheng Chi, Manuela Veloso, and Shuran Song · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware
Tony Z. Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn · 2023
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Gr-2: A generative video-language-action model with web-scale knowledge for robot manipulation
Chi-Lam Cheang, Guangzeng Chen, Ya Jing, Tao Kong, Hang Li, Yifeng Li, Yuxiao Liu, Hongtao Wu, Jiafeng Xu, Yichu Yang, et al · 2024
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Rvt-2: Learning precise manipulation from few demonstrations
Ankit Goyal, Valts Blukis, Jie Xu, Yijie Guo, Yu-Wei Chao, and Dieter Fox · 2024
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Large-scale actionless video pre-training via discrete diffusion for efficient policy learning
Haoran He, Chenjia Bai, Ling Pan, Weinan Zhang, Bin Zhao, and Xuelong Li · 2024
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Yuanchen Ju, Kaizhe Hu, Guowei Zhang, Gu Zhang, Mingrun Jiang, and Huazhe Xu · 2024
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Decisionnce: Embodied multimodal representations via implicit preference learning
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Libero: Benchmarking knowledge transfer for lifelong robot learning
Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, and Peter Stone · 2024
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Task-conditioned adaptation of visual features in multi-task policy learning
Pierre Marza, Laetitia Matignon, Olivier Simonin, and Christian Wolf · 2024
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Theia: Distilling diverse vision foundation models for robot learning
Jinghuan Shang, Karl Schmeckpeper, Brandon B May, Maria Vittoria Minniti, Tarik Kelestemur, David Watkins, and Laura Herlant · 2024
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General flow as foundation affordance for scalable robot learning
Chengbo Yuan, Chuan Wen, Tong Zhang, and Yang Gao · 2024
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Yanjie Ze, Gu Zhang, Kangning Zhang, Chenyuan Hu, Muhan Wang, and Huazhe Xu · 2024
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Learning manipulation by predicting interaction
Jia Zeng, Qingwen Bu, Bangjun Wang, Wenke Xia, Li Chen, Hao Dong, Haoming Song, Dong Wang, Di Hu, Ping Luo, et al · 2024
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