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A robot's ability to act is fundamentally constrained by what it can perceive.
Curl: Contrastive unsupervised representations for reinforcement learning
M. Laskin, A. Srinivas, and P. Abbeel · 2003
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Reinforcement learming with augmented data
M. Laskin, K. Lee, A. Stooke, L. Pinto, P. Abbeel, and A. Srinivas · 2004
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Large scale online learning of image similarity through ranking
G. Chechik, V. Sharma, U. Shalit, and S. Bengio · 2010
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Mujoco: A physics engine for model-based control
E. Todorov, T. Erez, and Y. Tassa · 2012
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Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2013
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Deterministic policy gradient algorithms
D. Silver, G. Lever, N. Heess, T. Degris, D. Wierstra, and M. Riedmiller · 2014
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U-net: Convolutional networks for biomedical image segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
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Deep spatial autoencoders for visuomotor learning
C. Finn, X. Y. Tan, Y. Duan, T. Darrell, S. Levine, and P. Abbeel · 2016
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Yolo9000: Better, faster, stronger
J. Redmon and A. Farhadi · 2016
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Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes
Y. Xiang, T. Schmidt, V. Narayanan, and D. Fox · 2017
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Bb8: A scalable, accurate, robust to partial occlusion method for predicting the 3d poses of challenging objects without using depth
M. Rad and V. Lepetit · 2017
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Time-contrastive networks: Self-supervised learning from multi-view observation
P. Sermanet, C. Lynch, J. Hsu, and S. Levine · 2017
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beta-vae: Learning basic visual concepts with a constrained variational framework
I. Higgins, L. Matthey, A. Pal, C. Burgess, X. Glorot, M. M. Botvinick, S. Mohamed, and A. Lerchner · 2017
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Google vizier: A service for black-box optimization
D. Golovin, B. Solnik, S. Moitra, G. Kochanski, J. Karro, and D. Sculley · 2017
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Unsupervised geometry-aware representation learning for 3d human pose estimation
H. Rhodin, M. Salzmann, and P. Fua · 2018
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Representation learning with contrastive predictive coding
A. van den Oord, Y. Li, and O. Vinyals · 2018
Self-supervised 3d keypoint learning for ego-motion estimation
J. Tang, R. Ambrus, V. Guizilini, S. Pillai, H. Kim, and A. Gaidon · 2019
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A practical approach to insertion with variable socket position using deep reinforcement learning
M. Vecerik, O. Sushkov, D. Barker, T. Rothörl, T. Hester, and J. Scholz · 2019
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Making sense of vision and touch: Self-supervised learning of multimodal representations for contact-rich tasks
M. A. Lee, Y. Zhu, K. Srinivasan, P. Shah, S. Savarese, L. Fei-Fei, A. Garg, and J. Bohg · 2019
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Monocular human pose estimation: A survey of deep learning-based methods
Y. Chen, Y. Tian, and M. He · 2019
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kpam: Keypoint affordances for category-level robotic manipulation
L. Manuelli, W. Gao, P. R. Florence, and R. Tedrake · 2019
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Deepim: Deep iterative matching for 6d pose estimation
Y. Li, G. Wang, X. Ji, Y. Xiang, and D. Fox · 2018
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Matching features without descriptors: Implicitly matched interest points (imips)
T. Cieslewski, M. Bloesch, and D. Scaramuzza · 2018
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Discovery of latent 3d keypoints via end-to-end geometric reasoning
S. Suwajanakorn, N. Snavely, J. J. Tompson, and M. Norouzi · 2018
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Unsupervised learning of object landmarks through conditional image generation
T. Jakab, A. Gupta, H. Bilen, and A. Vedaldi · 2018
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Learning monocular 3d human pose estimation from multi-view images
H. Rhodin, J. Spörri, I. Katircioglu, V. Constantin, F. Meyer, E. Müller, M. Salzmann, and P. Fua · 2018
Cited alongside, same era.
Dense object nets: Learning dense visual object descriptors by and for robotic manipulation
P. Florence, L. Manuelli, and R. Tedrake · 2018
Cited alongside, same era.
Pvnet: Pixel-wise voting network for 6dof pose estimation
S. Peng, Y. Liu, Q. Huang, X. Zhou, and H. Bao · 2019
Cited alongside, same era.
Self-supervised correspondence in visuomotor policy learning
P. Florence, L. Manuelli, and R. Tedrake · 2019
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Graph-structured visual imitation
M. Sieb, X. Zhou, A. M. Huang, O. Kroemer, and K. Fragkiadaki · 2019
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Keypose: Multi-view 3d labeling and keypoint estimation for transparent objects
X. Liu, R. Jonschkowski, A. Angelova, and K. Konolige · 2020
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Learning to see before learning to act: Visual pre-training for manipulation
L. Yen-Chen, A. Zeng, S. Song, P. Isola, and T.-Y. Lin · 2020
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Image augmentation is all you need: Regularizing deep reinforcement learning from pixels
I. Kostrikov, D. Yarats, and R. Fergus · 2020
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Epos: Estimating 6d pose of objects with symmetries
T. Hodan, D. Baráth, and J. Matas · 2020
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