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In this work, we introduce PianoMime, a framework for training a piano-playing agent using internet demonstrations.
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J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov · 2017
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X. B. Peng, P. Abbeel, S. Levine, and M. Van de Panne · 2018
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T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine · 2018
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F. Torabi, G. Warnell, and P. Stone · 2019
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B. Scholz · 2019
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L. Fan, G. Wang, Y. Jiang, A. Mandlekar, Y. Yang, H. Zhu, A. Tang, D.-A. Huang, Y. Zhu, and A. Anandkumar · 2022
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K. Grauman, A. Westbury, E. Byrne, Z. Chavis, A. Furnari, R. Girdhar, J. Hamburger, H. Jiang, M. Liu, X. Liu, et al · 2022
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Vip: Towards universal visual reward and representation via value-implicit pre-training
Y. J. Ma, S. Sodhani, D. Jayaraman, O. Bastani, V. Kumar, and A. Zhang · 2022
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H. Xu, Y. Luo, S. Wang, T. Darrell, and R. Calandra · 2022
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Physics-based dexterous manipulations with estimated hand poses and residual reinforcement learning
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X. B. Peng, E. Coumans, T. Zhang, T.-W. Lee, J. Tan, and S. Levine · 2020
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J. Ho, A. Jain, and P. Abbeel · 2020
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Learning fine-grained bimanual manipulation with low-cost hardware
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Pink: Python inverse kinematics based on Pinocchio, 2024
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