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PointGoal Navigation is an embodied task that requires agents to navigate to a specified point in an unseen environment.
A simple framework for contrastive learning of visual representations
T. Chen, S. Kornblith, M. Norouzi, and G. Hinton · 2002
Earlier work this paper cites.
Improved baselines with momentum contrastive learning
X. Chen, H. Fan, R. Girshick, and K. He · 2003
Earlier work this paper cites.
Learning multiple tasks with kernel methods
T. Evgeniou, C. A. Micchelli, and M. Pontil · 2005
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
K. Cho, B. Van Merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio · 2014
Earlier work this paper cites.
Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
Earlier work this paper cites.
The 2014 nobel prize in physiology or medicine: a spatial model for cognitive neuroscience
N. Burgess · 2014
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Unsupervised learning of visual representations using videos
X. Wang and A. Gupta · 2015
Earlier work this paper cites.
Human-level control through deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, et al · 2015
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
D. Kingma and J. Ba · 2015
Earlier work this paper cites.
Context encoders: Feature learning by inpainting
D. Pathak, P. Krahenbuhl, J. Donahue, T. Darrell, and A. A. Efros · 2016
Earlier work this paper cites.
Unsupervised learning of visual representations by solving jigsaw puzzles
M. Noroozi and P. Favaro · 2016
Earlier work this paper cites.
Reinforcement learning with unsupervised auxiliary tasks
M. Jaderberg, V. Mnih, W. M. Czarnecki, T. Schaul, J. Z. Leibo, D. Silver, and K. Kavukcuoglu · 2016
Earlier work this paper cites.
Learning to navigate in complex environments
P. Mirowski, R. Pascanu, F. Viola, H. Soyer, A. J. Ballard, A. Banino, M. Denil, R. Goroshin, L. Sifre, K. Kavukcuoglu, D. Kumaran, and R. Hadsell · 2016
Earlier work this paper cites.
C. Beattie, J. Z. Leibo, D. Teplyashin, T. Ward, M. Wainwright, H. Küttler, A. Lefrancq, S. Green, V. Valdés, A. Sadik, J. Schrittwieser, K. Anderson, S. York, M. Cant, A. Cain, A. Bolton, S. Gaffney, H. King, D. Hassabis, S. Legg, and S. Petersen · 2016
Earlier work this paper cites.
Deep Residual Learning for Image Recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
High-dimensional continuous control using generalized advantage estimation
J. Schulman, P. Moritz, S. Levine, M. Jordan, and P. Abbeel · 2016
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Curiosity-driven exploration by self-supervised prediction
D. Pathak, P. Agrawal, A. A. Efros, and T. Darrell · 2017
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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
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Matterport3d: Learning from rgb-d data in indoor environments
A. Chang, A. Dai, T. Funkhouser, M. Halber, M. Niessner, M. Savva, S. Song, A. Zeng, and Y. Zhang · 2017
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Proximal policy optimization algorithms
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov · 2017
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Learning representations by maximizing mutual information across views
P. Bachman, R. D. Hjelm, and W. Buchwalter · 2019
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Y. Tian, D. Krishnan, and P. Isola · 2019
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Momentum contrast for unsupervised visual representation learning
K. He, H. Fan, Y. Wu, S. Xie, and R. Girshick · 2019
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Self-supervised learning of pretext-invariant representations
I. Misra and L. van der Maaten · 2019
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Shaping Belief States with Generative Environment Models for RL
K. Gregor, D. J. Rezende, F. Besse, Y. Wu, H. Merzic, and A. v. d. Oord · 2019
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A. v. d. Oord, Y. Li, and O. Vinyals · 2018
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Neural predictive belief representations
Z. D. Guo, M. G. Azar, B. Piot, B. A. Pires, T. Pohlen, and R. Munos · 2018
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Gibson env: Real-world perception for embodied agents
F. Xia, A. R. Zamir, Z. He, A. Sax, J. Malik, and S. Savarese · 2018
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Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
A. Kendall, R. Cipolla, and Y. Gal · 2018
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A. Sax, B. Emi, A. R. Zamir, L. Guibas, S. Savarese, and J. Malik · 2018
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Taskonomy: Disentangling task transfer learning
A. R. Zamir, A. Sax, W. Shen, L. J. Guibas, J. Malik, and S. Savarese · 2018
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On evaluation of embodied navigation agents
P. Anderson, A. X. Chang, D. S. Chaplot, A. Dosovitskiy, S. Gupta, V. Koltun, J. Kosecka, J. Malik, R. Mottaghi, M. Savva, and A. R. Zamir · 2018
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Unsupervised state representation learning in atari
A. Anand, E. Racah, S. Ozair, Y. Bengio, M.-A. Côté, and R. D. Hjelm · 2019
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Adaptive auxiliary task weighting for reinforcement learning
X. Lin, H. Baweja, G. Kantor, and D. Held · 2019
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Learning deep representations by mutual information estimation and maximization
R. D. Hjelm, A. Fedorov, S. Lavoie-Marchildon, K. Grewal, P. Bachman, A. Trischler, and Y. Bengio · 2019
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Splitnet: Sim2sim and task2task transfer for embodied visual navigation
D. Gordon, A. Kadian, D. Parikh, J. Hoffman, and D. Batra · 2019
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Situational fusion of visual representation for visual navigation
W. B. Shen, D. Xu, Y. Zhu, L. J. Guibas, L. Fei-Fei, and S. Savarese · 2019
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Habitat: A platform for embodied AI research
M. Savva, A. Kadian, O. Maksymets, Y. Zhao, E. Wijmans, B. Jain, J. Straub, J. Liu, V. Koltun, J. Malik, et al · 2019
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Are we making real progress in simulated environments? measuring the sim2real gap in embodied visual navigation, 2019
A. Kadian, J. Truong, A. Gokaslan, A. Clegg, E. Wijmans, S. Lee, M. Savva, S. Chernova, and D. Batra · 2019
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DD-PPO: Learning near-perfect pointgoal navigators from 2.5 billion frames
E. Wijmans, A. Kadian, A. Morcos, S. Lee, I. Essa, D. Parikh, M. Savva, and D. Batra · 2020
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Learning to explore using active neural mapping
D. S. Chaplot, S. Gupta, D. Gandhi, A. Gupta, and R. Salakhutdinov · 2020
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