Fetching the paper…
Reading the bibliography…
Visual imitation learning provides a framework for learning complex manipulation behaviors by leveraging human demonstrations.
Imitation of facial and manual gestures by human neonates
A. N. Meltzoff and M. K. Moore · 1977
Earlier work this paper cites.
Newborn infants imitate adult facial gestures
A. N. Meltzoff and M. K. Moore · 1983
Earlier work this paper cites.
Alvinn: An autonomous land vehicle in a neural network
D. A. Pomerleau · 1989
Earlier work this paper cites.
Imitative learning of actions on objects by children, chimpanzees, and enculturated chimpanzees
M. Tomasello, S. Savage-Rumbaugh, and A. C. Kruger · 1993
Earlier work this paper cites.
Recognizing teleoperated manipulations
P. K. Pook and D. H. Ballard · 1993
Earlier work this paper cites.
Nonprehensile robotic manipulation: Controllability and planning
K. M. Lynch · 1996
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
Earlier work this paper cites.
Acquisition of probabilistic behavior decision model based on the interactive teaching method
T. I. M. I. H. Inoue, M. Inamura, and H. Inaba · 1999
Earlier work this paper cites.
Making reinforcement learning work on real robots
W. D. Smart · 2002
Earlier work this paper cites.
ISER , 2004
A. Ng, A. Coates, M. Diel, V. Ganapathi, J. Schulte, B. Tse, E. Berger, and E. Liang · 2004
Earlier work this paper cites.
A model of shared grasp affordances from demonstration
J. D. Sweeney and R. Grupen · 2007
Earlier work this paper cites.
Autonomous robotic pick-and-place of microobjects
Y. Zhang, B. K. Chen, X. Liu, and Y. Sun · 2009
Earlier work this paper cites.
A survey of robot learning from demonstration
B. D. Argall, S. Chernova, M. Veloso, and B. Browning · 2009
Earlier work this paper cites.
A reduction of imitation learning and structured prediction to no-regret online learning
S. Ross, G. Gordon, and D. Bagnell · 2011
Earlier work this paper cites.
Keyframe-based learning from demonstration
B. Akgun, M. Cakmak, K. Jiang, and A. L. Thomaz · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
Play, dreams and imitation in childhood , volume 25
J. Piaget · 2013
Cited alongside, same era.
Learning monocular reactive uav control in cluttered natural environments
S. Ross, N. Melik-Barkhudarov, K. S. Shankar, A. Wendel, D. Dey, J. A. Bagnell, and M. Hebert · 2013
Cited alongside, same era.
Learning strategies in table tennis using inverse reinforcement learning
K. Muelling, A. Boularias, B. Mohler, B. Schölkopf, and J. Peters · 2014
Cited alongside, same era.
Deepmpc: Learning deep latent features for model predictive control
I. Lenz, R. A. Knepper, and A. Saxena · 2015
Cited alongside, same era.
Unsupervised perceptual rewards for imitation learning
P. Sermanet, K. Xu, and S. Levine · 2016
Cited alongside, same era.
Multiple interactions made easy (mime): Large scale demonstrations data for imitation
P. Sharma, L. Mohan, L. Pinto, and A. Gupta · 2018
Later among the works it cites.
Nonprehensile dynamic manipulation: A survey
F. Ruggiero, V. Lippiello, and B. Siciliano · 2018
Later among the works it cites.
Asymmetric actor critic for image-based robot learning
L. Pinto, M. Andrychowicz, P. Welinder, W. Zaremba, and P. Abbeel · 2018
Later among the works it cites.
Dexpilot: Vision based teleoperation of dexterous robotic hand-arm system
A. Handa, K. Van Wyk, W. Yang, J. Liang, Y.-W. Chao, Q. Wan, S. Birchfield, N. Ratliff, and D. Fox · 2019
Later among the works it cites.
Autoaugment: Learning augmentation strategies from data
E. D. Cubuk, B. Zoph, D. Mane, V. Vasudevan, and Q. V. Le · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
M. Bojarski, D. Del Testa, D. Dworakowski, B. Firner, B. Flepp, P. Goyal, L. D. Jackel, M. Monfort, U. Muller, J. Zhang, et al · 2016
Cited alongside, same era.
Cad2rl: Real single-image flight without a single real image
F. Sadeghi and S. Levine · 2016
Cited alongside, same era.
Structure-from-Motion Revisited
J. L. Schönberger and J.-M. Frahm · 2016
Cited alongside, same era.
Pixelwise View Selection for Unstructured Multi-View Stereo
J. L. Schönberger, E. Zheng, M. Pollefeys, and J.-M. Frahm · 2016
Cited alongside, same era.
Third-person imitation learning
B. C. Stadie, P. Abbeel, and I. Sutskever · 2017
Cited alongside, same era.
Autonomous robotic stone stacking with online next best object target pose planning
F. Furrer, M. Wermelinger, H. Yoshida, F. Gramazio, M. Kohler, R. Siegwart, and M. Hutter · 2017
Cited alongside, same era.
Domain randomization for transferring deep neural networks from simulation to the real world
J. Tobin, R. Fong, A. Ray, J. Schneider, W. Zaremba, and P. Abbeel · 2017
Cited alongside, same era.
D. Ho, E. Liang, X. Chen, I. Stoica, and P. Abbeel · 2019
Later among the works it cites.
Learning data augmentation strategies for object detection
B. Zoph, E. D. Cubuk, G. Ghiasi, T.-Y. Lin, J. Shlens, and Q. V. Le · 2019
Later among the works it cites.
Mixmatch: A holistic approach to semi-supervised learning
D. Berthelot, N. Carlini, I. Goodfellow, N. Papernot, A. Oliver, and C. A. Raffel · 2019
Later among the works it cites.
Unsupervised data augmentation for consistency training
Q. Xie, Z. Dai, E. Hovy, M.-T. Luong, and Q. V. Le · 2019
Later among the works it cites.
On the continuity of rotation representations in neural networks
Y. Zhou, C. Barnes, J. Lu, J. Yang, and H. Li · 2019
Later among the works it cites.
Grasping in the wild: Learning 6dof closed-loop grasping from low-cost demonstrations
S. Song, A. Zeng, J. Lee, and T. Funkhouser · 2020
Closest in time.
Reinforcement learning with augmented data
M. Laskin, K. Lee, A. Stooke, L. Pinto, P. Abbeel, and A. Srinivas · 2020
Closest in time.
Image augmentation is all you need: Regularizing deep reinforcement learning from pixels
I. Kostrikov, D. Yarats, and R. Fergus · 2020
Closest in time.
https://www.xarm.cc/products/xarm-7-2020
xarm 7 · 2020
Closest in time.
A simple framework for contrastive learning of visual representations
T. Chen, S. Kornblith, M. Norouzi, and G. Hinton · 2020
Closest in time.