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Perceptual understanding of the scene and the relationship between its different components is important for successful completion of robotic tasks.
P. Baldi, “Autoencoders, unsupervised learning, and deep architectures,” in Proceedings of ICML Workshop on Unsupervised and Transfer Learning , ser. Proceedings of Machine Learning Research, vol. 27. Bellevue, Washington, USA: PMLR, 02 Jul 2012, pp. 37–49. [Online]. Available: https://proceedings.mlr.press/v27/baldi12a.html
2012
Earlier work this paper cites.
Y. Yang and D. Ramanan, “Articulated human detection with flexible mixtures of parts,” IEEE transactions on pattern analysis and machine intelligence , vol. 35, no. 12, pp. 2878–2890, 2012
2012
Earlier work this paper cites.
X. Wang and A. Gupta, “Unsupervised learning of visual representations using videos,” in Proceedings of the IEEE international conference on computer vision , 2015, pp. 2794–2802
2015
Earlier work this paper cites.
C. Finn, X. Y. Tan, Y. Duan, T. Darrell, S. Levine, and P. Abbeel, “Deep spatial autoencoders for visuomotor learning,” in 2016 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2016, pp. 512–519
2016
Earlier work this paper cites.
A. Odena, V. Dumoulin, and C. Olah, “Deconvolution and checkerboard artifacts,” Distill , vol. 1, no. 10, p. e3, 2016
2016
Earlier work this paper cites.
E. Coumans and Y. Bai, “Pybullet, a python module for physics simulation for games, robotics and machine learning,” 2016
2016
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” in Advances in neural information processing systems , 2017, pp. 5998–6008
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
C. Devin, P. Abbeel, T. Darrell, and S. Levine, “Deep object-centric representations for generalizable robot learning,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 7111–7118
2018
Earlier work this paper cites.
2018
Cited alongside, same era.
2019
Cited alongside, same era.
P. Florence, L. Manuelli, and R. Tedrake, “Self-supervised correspondence in visuomotor policy learning,” IEEE Robotics and Automation Letters , vol. 5, no. 2, pp. 492–499, 2019
2019
Cited alongside, same era.
2019
Cited alongside, same era.
M. A. Lee, Y. Zhu, P. Zachares, M. Tan, K. Srinivasan, S. Savarese, L. Fei-Fei, A. Garg, and J. Bohg, “Making sense of vision and touch: Learning multimodal representations for contact-rich tasks,” IEEE Transactions on Robotics , vol. 36, no. 3, pp. 582–596, 2020
2020
Later among the works it cites.
X. Deng, Y. Xiang, A. Mousavian, C. Eppner, T. Bretl, and D. Fox, “Self-supervised 6d object pose estimation for robot manipulation,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2020, pp. 3665–3671
2020
Later among the works it cites.
2020
Later among the works it cites.
W. Yuan, C. Paxton, K. Desingh, and D. Fox, “SORNet: Spatial object-centric representations for sequential manipulation,” in 5th Annual Conference on Robot Learning , 2021. [Online]. Available: https://openreview.net/forum?id=mOLu2rODIJF
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D. Wang, C. Devin, Q.-Z. Cai, F. Yu, and T. Darrell, “Deep object-centric policies for autonomous driving,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 8853–8859
2019
Cited alongside, same era.
2019
Cited alongside, same era.
2020
Cited alongside, same era.
F. Locatello, D. Weissenborn, T. Unterthiner, A. Mahendran, G. Heigold, J. Uszkoreit, A. Dosovitskiy, and T. Kipf, “Object-centric learning with slot attention,” ser. NIPS’20. Red Hook, NY, USA: Curran Associates Inc., 2020
2020
Cited alongside, same era.
2020
Cited alongside, same era.
R. Jonschkowski, A. Stone, J. T. Barron, A. Gordon, K. Konolige, and A. Angelova, “What matters in unsupervised optical flow,” in Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part II 16 . Springer, 2020, pp. 557–572
2020
Cited alongside, same era.
T. Han, W. Xie, and A. Zisserman, “Self-supervised co-training for video representation learning,” in Neurips , 2020
2020
Cited alongside, same era.
2021
Later among the works it cites.
K. Zakka, A. Zeng, P. Florence, J. Tompson, J. Bohg, and D. Dwibedi, “Xirl: Cross-embodiment inverse reinforcement learning,” Conference on Robot Learning (CoRL) , 2021
2021
Later among the works it cites.
2021
Later among the works it cites.
P. Florence, C. Lynch, A. Zeng, O. Ramirez, A. Wahid, L. Downs, A. Wong, J. Lee, I. Mordatch, and J. Tompson, “Implicit behavioral cloning,” Conference on Robot Learning (CoRL) , November 2021
2021
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2021
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2022
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