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One of the key challenges in visual imitation learning is collecting large amounts of expert demonstrations for a given task.
Imitation of facial and manual gestures by human neonates
A. N. Meltzoff and M. K. Moore · 1977
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Newborn infants imitate adult facial gestures
A. N. Meltzoff and M. K. Moore · 1983
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Alvinn: An autonomous land vehicle in a neural network
D. A. Pomerleau · 1989
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Imitative learning of actions on objects by children, chimpanzees, and enculturated chimpanzees
M. Tomasello, S. Savage-Rumbaugh, and A. C. Kruger · 1993
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Reinforcement learning: A survey
L. P. Kaelbling, M. L. Littman, and A. W. Moore · 1996
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Improved baselines with momentum contrastive learning
X. Chen, H. Fan, R. Girshick, and K. He · 2003
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Apprenticeship learning via inverse reinforcement learning
P. Abbeel and A. Y. Ng · 2004
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Big self-supervised models are strong semi-supervised learners
T. Chen, S. Kornblith, K. Swersky, M. Norouzi, and G. Hinton · 2006
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Extracting and composing robust features with denoising autoencoders
P. Vincent, H. Larochelle, Y. Bengio, and P.-A. Manzagol · 2008
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A survey of robot learning from demonstration
B. D. Argall, S. Chernova, M. Veloso, and B. Browning · 2009
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Adapting visual category models to new domains
K. Saenko, B. Kulis, M. Fritz, and T. Darrell · 2010
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Unbiased look at dataset bias
A. Torralba and A. A. Efros · 2011
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Where science starts: Spontaneous experiments in preschoolers’ exploratory play
C. Cook, N. D. Goodman, and L. E. Schulz · 2011
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A reduction of imitation learning and structured prediction to no-regret online learning
S. Ross, G. Gordon, and D. Bagnell · 2011
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2012
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Play, dreams and imitation in childhood , volume 25
J. Piaget · 2013
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The impact of pretend play on children’s development: A review of the evidence
A. S. Lillard, M. D. Lerner, E. J. Hopkins, R. A. Dore, E. D. Smith, and C. M. Palmquist · 2013
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Actor-mimic: Deep multitask and transfer reinforcement learning
E. Parisotto, J. L. Ba, and R. Salakhutdinov · 2015
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Discriminative unsupervised feature learning with exemplar convolutional neural networks, 2015
A. Dosovitskiy, P. Fischer, J. T. Springenberg, M. Riedmiller, and T. Brox · 2015
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Learning state representations with robotic priors
R. Jonschkowski and O. Brock · 2015
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Generative adversarial imitation learning
J. Ho and S. Ermon · 2016
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Unsupervised perceptual rewards for imitation learning
P. Sermanet, K. Xu, and S. Levine · 2016
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Unsupervised visual representation learning by context prediction, 2016
C. Doersch, A. Gupta, and A. A. Efros · 2016
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Shuffle and learn: Unsupervised learning using temporal order verification, 2016
Behavioral cloning from observation
F. Torabi, G. Warnell, and P. Stone · 2018
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Reinforcement and imitation learning for diverse visuomotor skills
Y. Zhu, Z. Wang, J. Merel, A. A. Rusu, T. Erez, S. Cabi, S. Tunyasuvunakool, J. Kramár, R. Hadsell, N. de Freitas, and N. Heess · 2018
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Unsupervised feature learning via non-parametric instance-level discrimination, 2018
Z. Wu, Y. Xiong, S. Yu, and D. Lin · 2018
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Representation learning with contrastive predictive coding
A. v. d. Oord, Y. Li, and O. Vinyals · 2018
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I. Misra, C. L. Zitnick, and M. Hebert · 2016
Cited alongside, same era.
Deep spatial autoencoders for visuomotor learning
C. Finn, X. Y. Tan, Y. Duan, T. Darrell, S. Levine, and P. Abbeel · 2016
Cited alongside, same era.
Third-person imitation learning
B. C. Stadie, P. Abbeel, and I. Sutskever · 2017
Cited alongside, same era.
One-shot imitation learning
Y. Duan, M. Andrychowicz, B. Stadie, O. J. Ho, J. Schneider, I. Sutskever, P. Abbeel, and W. Zaremba · 2017
Cited alongside, same era.
Learning higher-order generalizations through free play: Evidence from 2-and 3-year-old children
Z. L. Sim and F. Xu · 2017
Cited alongside, same era.
The role of play in children’s development: a review of the evidence
D. Whitebread, D. Neale, H. Jensen, C. Liu, S. L. Solis, E. Hopkins, K. Hirsh-Pasek, and J. Zosh · 2017
Cited alongside, same era.
Learning modular neural network policies for multi-task and multi-robot transfer
C. Devin, A. Gupta, T. Darrell, P. Abbeel, and S. Levine · 2017
Cited alongside, same era.
L. Zhang and X. Gao · 2019
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S4l: Self-supervised semi-supervised learning, 2019
X. Zhai, A. Oliver, A. Kolesnikov, and L. Beyer · 2019
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Unsupervised domain adaptation through self-supervision, 2019
Y. Sun, E. Tzeng, T. Darrell, and A. A. Efros · 2019
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Grasping in the wild: Learning 6dof closed-loop grasping from low-cost demonstrations
S. Song, A. Zeng, J. Lee, and T. Funkhouser · 2020
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Visual imitation made easy
S. Young, D. Gandhi, S. Tulsiani, A. Gupta, P. Abbeel, and L. Pinto · 2020
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Learning latent plans from play
C. Lynch, M. Khansari, T. Xiao, V. Kumar, J. Tompson, S. Levine, and P. Sermanet · 2020
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Bootstrap your own latent: A new approach to self-supervised learning
J.-B. Grill, F. Strub, F. Altché, C. Tallec, P. H. Richemond, E. Buchatskaya, C. Doersch, B. A. Pires, Z. D. Guo, M. G. Azar, et al · 2020
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Unsupervised learning of visual features by contrasting cluster assignments
M. Caron, I. Misra, J. Mairal, P. Goyal, P. Bojanowski, and A. Joulin · 2020
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Learning latent representations to influence multi-agent interaction
A. Xie, D. P. Losey, R. Tolsma, C. Finn, and D. Sadigh · 2020
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Demystifying contrastive self-supervised learning: Invariances, augmentations and dataset biases
S. Purushwalkam and A. Gupta · 2020
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Decoupling representation learning from reinforcement learning
A. Stooke, K. Lee, P. Abbeel, and M. Laskin · 2020
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Reinforcement learning with prototypical representations
D. Yarats, R. Fergus, A. Lazaric, and L. Pinto · 2021
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Low dimensional state representation learning with robotics priors in continuous action spaces, 2021
N. Botteghi, K. Alaa, M. Poel, B. Sirmacek, C. Brune, A. Mersha, and S. Stramigioli · 2021
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Representation matters: Improving perception and exploration for robotics, 2021
M. Wulfmeier, A. Byravan, T. Hertweck, I. Higgins, A. Gupta, T. Kulkarni, M. Reynolds, D. Teplyashin, R. Hafner, T. Lampe, and M. Riedmiller · 2021
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Learning a state representation and navigation in cluttered and dynamic environments
D. Hoeller, L. Wellhausen, F. Farshidian, and M. Hutter · 2021
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