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Combining optimal control and learning for visual navigation in novel environments
S. Bansal, V. Tolani, S. Gupta, J. Malik, and C. Tomlin · 1903
Earlier work this paper cites.
Neural networks and the bias/variance dilemma
S. Geman, E. Bienenstock, and R. Doursat · 1992
Earlier work this paper cites.
Forward models: Supervised learning with a distal teacher
M. I. Jordan and D. E. Rumelhart · 1992
Earlier work this paper cites.
A model of inductive bias learning
J. Baxter · 2000
Earlier work this paper cites.
Reducing the dimensionality of data with neural networks
G. E. Hinton and R. R. Salakhutdinov · 2006
Earlier work this paper cites.
Ten-fold improvement in visual odometry using landmark matching
Z. Zhu, T. Oskiper, S. Samarasekera, R. Kumar, and H. S. Sawhney · 2007
Earlier work this paper cites.
Springer Handbook of Robotics
B. Siciliano and O. Khatib · 2007
Earlier work this paper cites.
Extracting and composing robust features with denoising autoencoders
P. Vincent, H. Larochelle, Y. Bengio, and P.-A. Manzagol · 2008
Earlier work this paper cites.
ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
Intrinsic shape signatures: A shape descriptor for 3d object recognition
Y. Zhong · 2009
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.
Indoor Segmentation and Support Inference from RGBD Images , pages 746–760
N. Silberman, D. Hoiem, P. Kohli, and R. Fergus · 2012
Earlier work this paper cites.
Representation learning: A review and new perspectives
Y. Bengio, A. Courville, and P. Vincent · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2013
Earlier work this paper cites.
Depth map prediction from a single image using a multi-scale deep network
D. Eigen, C. Puhrsch, and R. Fergus · 2014
Earlier work this paper cites.
Ground plane estimation using a hidden markov model
R. Dragon and L. Van Gool · 2014
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, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis · 2015
Earlier work this paper cites.
End-to-end training of deep visuomotor policies
S. Levine, C. Finn, T. Darrell, and P. Abbeel · 2015
Earlier work this paper cites.
Understanding mid-level representations in visual processing
J. W. Peirce · 2015
Earlier work this paper cites.
R. B. Girshick · 2015
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Unsupervised visual representation learning by context prediction
C. Doersch, A. Gupta, and A. A. Efros · 2015
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ORB-SLAM: a versatile and accurate monocular SLAM system
M. J. M. M. Mur-Artal, Raúl and J. D. Tardós · 2015
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Cited alongside, same era.
High-dimensional continuous control using generalized advantage estimation
J. Schulman, P. Moritz, S. Levine, M. I. Jordan, and P. Abbeel · 2015
Cited alongside, same era.
On offline evaluation of vision-based driving models
F. Codevilla, A. López, V. Koltun, and A. Dosovitskiy · 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
Later among the works it cites.
Gibson Env: Real-world perception for embodied agents
F. Xia, A. Zamir, Z.-Y. He, A. Sax, J. Malik, and S. Savarese · 2018
Later among the works it cites.
Taskonomy: Disentangling task transfer learning
A. R. Zamir, A. Sax, W. B. Shen, L. J. Guibas, J. Malik, and S. Savarese · 2018
Later among the works it cites.
Openpose: Realtime multi-person 2d pose estimation using part affinity fields
Z. Cao, G. Hidalgo, T. Simon, S. Wei, and Y. Sheikh · 2018
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D. Amodei, C. Olah, J. Steinhardt, P. F. Christiano, J. Schulman, and D. Mané · 2016
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Vizdoom: A doom-based AI research platform for visual reinforcement learning
M. Kempka, M. Wydmuch, G. Runc, J. Toczek, and W. Jaskowski · 2016
Cited alongside, same era.
Unsupervised learning of visual representations by solving jigsaw puzzles
M. Noroozi and P. Favaro · 2016
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Learning to act by predicting the future
A. Dosovitskiy and V. Koltun · 2016
Cited alongside, same era.
Learning to poke by poking: Experiential learning of intuitive physics
P. Agrawal, A. Nair, P. Abbeel, J. Malik, and S. Levine · 2016
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Learning state representation for deep actor-critic control
J. Munk, J. Kober, and R. Babuška · 2016
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Loss is its own reward: Self-supervision for reinforcement learning
E. Shelhamer, P. Mahmoudieh, M. Argus, and T. Darrell · 2016
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Representation learning with contrastive predictive coding
A. van den Oord, Y. Li, and O. Vinyals · 2018
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S-RL toolbox: Environments, datasets and evaluation metrics for state representation learning
A. Raffin, A. Hill, R. Traoré, T. Lesort, N. D. Rodríguez, and D. Filliat · 2018
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Driving policy transfer via modularity and abstraction
M. Müller, A. Dosovitskiy, B. Ghanem, and V. Koltun · 2018
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Visual representations for semantic target driven navigation
A. Mousavian, A. Toshev, M. Fiser, J. Kosecka, and J. Davidson · 2018
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Visual semantic navigation using scene priors
W. Yang, X. Wang, A. Farhadi, A. Gupta, and R. Mottaghi · 2018
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Dense object nets: Learning dense visual object descriptors by and for robotic manipulation
P. R. Florence, L. Manuelli, and R. Tedrake · 2018
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R. Jamiruddin, A. O. Sari, J. Shabbir, and T. Anwer · 2018
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On evaluation of embodied navigation agents
P. Anderson, A. Chang, D. S. Chaplot, A. Dosovitskiy, S. Gupta, V. Koltun, J. Kosecka, J. Malik, R. Mottaghi, M. Savva, et al · 2018
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Visual memory for robust path following
A. Kumar, S. Gupta, D. Fouhey, S. Levine, and J. Malik · 2018
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Habitat: A platform for embodied ai research
O. Y. Z. E. W. B. J. J. S. J. L. V. K. J. M. D. P. Manolis Savva*, Abhishek Kadian* and D. Batra · 2019
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Does computer vision matter for action?
B. Zhou, P. Krähenbühl, and V. Koltun · 2019
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Habitat: A Platform for Embodied AI Research
Manolis Savva*, Abhishek Kadian*, Oleksandr Maksymets*, Y. Zhao, E. Wijmans, B. Jain, J. Straub, J. Liu, V. Koltun, J. Malik, D. Parikh, and D. Batra · 2019
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Controlling the false discovery rate: A practical and powerful approach to multiple testing
Y. Benjamini and Y. Hochberg · 2019
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