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Recent studies on visual reinforcement learning (visual RL) have explored the use of 3D visual representations.
The optimal control of partially observable markov processes over a finite horizon
Richard D Smallwood and Edward J Sondik · 1973
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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Playing atari with deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Sim-to-real transfer of robotic control with dynamics randomization
Xue Bin Peng, Marcin Andrychowicz, Wojciech Zaremba, and P. Abbeel · 2017
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Asymmetric actor critic for image-based robot learning
Lerrel Pinto, Marcin Andrychowicz, Peter Welinder, Wojciech Zaremba, and P. Abbeel · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Domain randomization for transferring deep neural networks from simulation to the real world
Joshua Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and P. Abbeel · 2017
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Soft actor-critic algorithms and applications
Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, et al · 2018
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Qt-opt: Scalable deep reinforcement learning for vision-based robotic manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, and Sergey Levine · 2018
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Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, et al · 2018
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Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving
Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark E. Campbell, and Kilian Q. Weinberger · 2018
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Reinforcement and imitation learning for diverse visuomotor skills
Yuke Zhu, Ziyun Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, and Nicolas Manfred Otto Heess · 2018
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Dota 2 with large scale deep reinforcement learning
Christopher Berner, Greg Brockman, Brooke Chan, Vicki Cheung, Przemysław Dębiak, Christy Dennison, David Farhi, Quirin Fischer, Shariq Hashme, Chris Hesse, et al · 2019
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4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Bongsoo Choy, JunYoung Gwak, and Silvio Savarese · 2019
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Robonet: Large-scale multi-robot learning
Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, and Chelsea Finn · 2019
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Dream to control: Learning behaviors by latent imagination
Danijar Hafner, Timothy Lillicrap, Jimmy Ba, and Mohammad Norouzi · 2019
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Learning latent dynamics for planning from pixels
Danijar Hafner, Timothy Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, and James Davidson · 2019
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Active domain randomization
Bhairav Mehta, Manfred Diaz, Florian Golemo, Christopher Joseph Pal, and Liam Paull · 2019
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Kpconv: Flexible and deformable convolution for point clouds
Hugues Thomas, C. Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, and Leonidas J. Guibas · 2019
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Densefusion: 6d object pose estimation by iterative dense fusion
Chen Wang, Danfei Xu, Yuke Zhu, Roberto Martín-Martín, Cewu Lu, Li Fei-Fei, and Silvio Savarese · 2019
Cited alongside, same era.
Improving sample efficiency in model-free reinforcement learning from images
Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, and Rob Fergus · 2019
Cited alongside, same era.
Mastering atari with discrete world models
Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, and Jimmy Ba · 2020
Cited alongside, same era.
Pvn3d: A deep point-wise 3d keypoints voting network for 6dof pose estimation
Yisheng He, Wei Sun, Haibin Huang, Jianran Liu, Haoqiang Fan, and Jian Sun · 2020
Cited alongside, same era.
Image augmentation is all you need: Regularizing deep reinforcement learning from pixels
Ilya Kostrikov, Denis Yarats, and Rob Fergus · 2020
Cited alongside, same era.
Contact-graspnet: Efficient 6-dof grasp generation in cluttered scenes
Martin Sundermeyer, Arsalan Mousavian, Rudolph Triebel, and Dieter Fox · 2021
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Mastering visual continuous control: Improved data-augmented reinforcement learning
Denis Yarats, Rob Fergus, Alessandro Lazaric, and Lerrel Pinto · 2021
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A system for general in-hand object re-orientation
Tao Chen, Jie Xu, and Pulkit Agrawal · 2022
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Flowbot3d: Learning 3d articulation flow to manipulate articulated objects
Ben Eisner, Harry Zhang, and David Held · 2022
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Temporal difference learning for model predictive control
Nicklas Hansen, Xiaolong Wang, and Hao Su · 2022
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Reinforcement learning with augmented data
Misha Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, and Aravind Srinivas · 2020
Cited alongside, same era.
Planning to explore via self-supervised world models
Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, P. Abbeel, Danijar Hafner, and Deepak Pathak · 2020
Cited alongside, same era.
Curl: Contrastive unsupervised representations for reinforcement learning
Aravind Srinivas, Michael Laskin, and Pieter Abbeel · 2020
Cited alongside, same era.
Searching efficient 3d architectures with sparse point-voxel convolution
Haotian* Tang, Zhijian* Liu, Shengyu Zhao, Yujun Lin, Ji Lin, Hanrui Wang, and Song Han · 2020
Cited alongside, same era.
Mastering complex control in moba games with deep reinforcement learning
Deheng Ye, Zhao Liu, Mingfei Sun, Bei Shi, Peilin Zhao, Hao Wu, Hongsheng Yu, Shaojie Yang, Xipeng Wu, Qingwei Guo, et al · 2020
Cited alongside, same era.
Transporter networks: Rearranging the visual world for robotic manipulation
Andy Zeng, Peter R. Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, and Johnny Lee · 2020
Cited alongside, same era.
Point transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip H. S. Torr, and Vladlen Koltun · 2020
Cited alongside, same era.
Coarse-to-fine q-attention: Efficient learning for visual robotic manipulation via discretisation
Stephen James, Kentaro Wada, Tristan Laidlow, and Andrew J. Davison · 2022
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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 · 2022
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Frame mining: a free lunch for learning robotic manipulation from 3d point clouds
Minghua Liu, Xuanlin Li, Zhan Ling, Yangyan Li, and Hao Su · 2022
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R3m: A universal visual representation for robot manipulation
Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, and Abhi Gupta · 2022
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The unsurprising effectiveness of pre-trained vision models for control
Simone Parisi, Aravind Rajeswaran, Senthil Purushwalkam, and Abhinav Gupta · 2022
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Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, et al · 2022
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Perceiver-actor: A multi-task transformer for robotic manipulation
Mohit Shridhar, Lucas Manuelli, and Dieter Fox · 2022
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Softgroup for 3d instance segmentation on point clouds
Thang Vu, Kookhoi Kim, Tung Minh Luu, Xuan Thanh Nguyen, and Chang-Dong Yoo · 2022
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AdaAfford: Learning to adapt manipulation affordance for 3d articulated objects via few-shot interactions
Yian Wang, Ruihai Wu, Kaichun Mo, Jiaqi Ke, Qingnan Fan, Leonidas Guibas, and Hao Dong · 2022
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Learning generalizable dexterous manipulation from human grasp affordance
Yueh-Hua Wu, Jiashun Wang, and Xiaolong Wang · 2022
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Masked visual pre-training for motor control
Tete Xiao, Ilija Radosavovic, Trevor Darrell, and Jitendra Malik · 2022
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Learning to detect mobile objects from lidar scans without labels
Yurong You, Katie Z Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, and Kilian Q. Weinberger · 2022
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Visual reinforcement learning with self-supervised 3d representations
Yanjie Ze, Nicklas Hansen, Yinbo Chen, Mohit Jain, and Xiaolong Wang · 2022
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Learning hybrid actor-critic maps for 6d non-prehensile manipulation
Wenxuan Zhou, Bowen Jiang, Fan Yang, Chris Paxton, and David Held · 2023
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