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Research on Inverse Reinforcement Learning (IRL) from third-person videos has shown encouraging results on removing the need for manual reward design for robotic tasks.
Alvinn: An autonomous land vehicle in a neural network
D. A. Pomerleau · 1988
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Robot learning from demonstration
C. G. Atkeson and S. Schaal · 1997
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Algorithms for inverse reinforcement learning
A. Y. Ng, S. J. Russell, et al · 2000
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Apprenticeship learning via inverse reinforcement learning
P. Abbeel and A. Y. Ng · 2004
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A survey of robot learning from demonstration
B. Argall, S. Chernova, M. Veloso, and B. Browning · 2009
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Temporal logic motion planning for dynamic robots
G. Fainekos, A. Girard, H. Kress-Gazit, and G. J. Pappas · 2009
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Combined task and motion planning through an extensible planner-independent interface layer
S. Srivastava, E. Fang, L. Riano, R. Chitnis, S. Russell, and P. Abbeel · 2014
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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Human-level control through deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. A. Riedmiller, A. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis · 2015
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ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
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Interaction networks for learning about objects, relations and physics
P. Battaglia, R. Pascanu, M. Lai, D. Jimenez Rezende, et al · 2016
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Generative adversarial imitation learning
J. Ho and S. Ermon · 2016
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Learning robust rewards with adversarial inverse reinforcement learning
J. Fu, K. Luo, and S. Levine · 2017
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Scene graph generation by iterative message passing
D. Xu, Y. Zhu, C. B. Choy, and L. Fei-Fei · 2017
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Scene graph generation from objects, phrases and region captions
Y. Li, W. Ouyang, B. Zhou, K. Wang, and X. Wang · 2017
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Visual interaction networks: Learning a physics simulator from video
N. Watters, D. Zoran, T. Weber, P. Battaglia, R. Pascanu, and A. Tacchetti · 2017
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Learning invariant feature spaces to transfer skills with reinforcement learning
A. Gupta, C. Devin, Y. Liu, P. Abbeel, and S. Levine · 2017
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Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection
S. Levine, P. Pastor, A. Krizhevsky, and D. Quillen · 2018
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Zero-shot visual imitation
D. Pathak, P. Mahmoudieh, G. Luo, P. Agrawal, D. Chen, Y. Shentu, E. Shelhamer, J. Malik, A. A. Efros, and T. Darrell · 2018
Earlier work this paper cites.
Behavioral cloning from observation
F. Torabi, G. Warnell, and P. Stone · 2018
Cited alongside, same era.
Playing hard exploration games by watching youtube
Y. Aytar, T. Pfaff, D. Budden, T. Paine, Z. Wang, and N. de Freitas · 2018
Cited alongside, same era.
Generative adversarial imitation from observation
F. Torabi, G. Warnell, and P. Stone · 2018
Cited alongside, same era.
Graph networks as learnable physics engines for inference and control
A. Sanchez-Gonzalez, N. Heess, J. T. Springenberg, J. Merel, M. Riedmiller, R. Hadsell, and P. Battaglia · 2018
Cited alongside, same era.
Soft actor-critic: Off-policy maximum entropy deep reinforcement, 2018
T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine · 2018
Cited alongside, same era.
Time-contrastive networks: Self-supervised learning from video
Graph-structured visual imitation
M. Sieb, Z. Xian, A. Huang, O. Kroemer, and K. Fragkiadaki · 2020
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Dynamic graph warping transformer for video alignment
J. Wang, Y. Long, M. Pagnucco, and Y. Song · 2020
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Understanding human hands in contact at internet scale
D. Shan, J. Geng, M. Shu, and D. F. Fouhey · 2020
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Image augmentation is all you need: Regularizing deep reinforcement learning from pixels
D. Yarats, I. Kostrikov, and R. Fergus · 2020
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State-only imitation learning for dexterous manipulation
I. Radosavovic, X. Wang, L. Pinto, and J. Malik · 2021
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Learning by watching: Physical imitation of manipulation skills from human videos
H. Xiong, Q. Li, Y.-C. Chen, H. Bharadhwaj, S. Sinha, and A. Garg · 2021
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P. Sermanet, C. Lynch, Y. Chebotar, J. Hsu, E. Jang, S. Schaal, S. Levine, and G. Brain · 2018
Cited alongside, same era.
Temporal cycle-consistency learning
D. Dwibedi, Y. Aytar, J. Tompson, P. Sermanet, and A. Zisserman · 2019
Cited alongside, same era.
Cognitive mapping and planning for visual navigation
S. Gupta, V. Tolani, J. Davidson, S. Levine, R. Sukthankar, and J. Malik · 2019
Cited alongside, same era.
Visual semantic navigation using scene priors
W. Yang, X. Wang, A. Farhadi, A. K. Gupta, and R. Mottaghi · 2019
Cited alongside, same era.
Compositional video prediction
Y. Ye, M. Singh, A. Gupta, and S. Tulsiani · 2019
Cited alongside, same era.
Learning compositional koopman operators for model-based control
Y. Li, H. He, J. Wu, D. Katabi, and A. Torralba · 2019
Cited alongside, same era.
Learning dexterous in-hand manipulation
O. M. Andrychowicz, B. Baker, M. Chociej, R. Józefowicz, B. McGrew, J. W. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray, J. Schneider, S. Sidor, J. Tobin, P. Welinder, L. Weng, and W. Zaremba · 2020
Cited alongside, same era.
Later among the works it cites.
Generalizable imitation learning from observation via inferring goal proximity
Y. Lee, A. Szot, S.-H. Sun, and J. J. Lim · 2021
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Learning generalizable robotic reward functions from” in-the-wild” human videos
A. S. Chen, S. Nair, and C. Finn · 2021
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Cross-domain imitation learning via optimal transport
A. Fickinger, S. Cohen, S. Russell, and B. Amos · 2021
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Dexmv: Imitation learning for dexterous manipulation from human videos
Y. Qin, Y.-H. Wu, S. Liu, H. Jiang, R. Yang, Y. Fu, and X. Wang · 2021
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Hierarchical planning for long-horizon manipulation with geometric and symbolic scene graphs
Y. Zhu, J. Tremblay, S. Birchfield, and Y. Zhu · 2021
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Learning long-term visual dynamics with region proposal interaction networks
H. Qi, X. Wang, D. Pathak, Y. Ma, and J. Malik · 2021
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Learning by aligning videos in time
S. Haresh, S. Kumar, H. Coskun, S. N. Syed, A. Konin, Z. Zia, and Q.-H. Tran · 2021
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Learning to align sequential actions in the wild
W. Liu, B. Tekin, H. Coskun, V. Vineet, P. Fua, and M. Pollefeys · 2021
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Representation learning via global temporal alignment and cycle-consistency
I. Hadji, K. G. Derpanis, and A. D. Jepson · 2021
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Stabilizing deep q-learning with convnets and vision transformers under data augmentation
N. Hansen, H. Su, and X. Wang · 2021
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Xirl: Cross-embodiment inverse reinforcement learning
K. Zakka, A. Zeng, P. Florence, J. Tompson, J. Bohg, and D. Dwibedi · 2022
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Dexterous imitation made easy: A learning-based framework for efficient dexterous manipulation
S. P. Arunachalam, S. Silwal, B. Evans, and L. Pinto · 2022
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Look closer: Bridging egocentric and third-person views with transformers for robotic manipulation
R. Jangir, N. Hansen, S. Ghosal, M. Jain, and X. Wang · 2022
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