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To teach robots skills, it is crucial to obtain data with supervision.
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T. Schmidt, R. Newcombe, and D. Fox, “Self-supervised visual descriptor learning for dense correspondence,” IEEE Robotics and Automation Letters , vol. 2, no. 2, pp. 420–427, 2016
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2016
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J. Mahler, J. Liang, S. Niyaz, M. Laskey, R. Doan, X. Liu, J. A. Ojea, and K. Goldberg, “Dex-Net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics,” in Robotics: Science and Systems (RSS) , 2017
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2017
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2017
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2017
Cited alongside, same era.
2018
Later among the works it cites.
J. Tremblay, T. To, B. Sundaralingam, Y. Xiang, D. Fox, and S. Birchfield, “Deep object pose estimation for semantic robotic grasping of household objects,” in Conference on Robot Learning (CoRL) , 2018
2018
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2018
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P. Florence, L. Manuelli, and R. Tedrake, “Dense object nets: Learning dense visual object descriptors by and for robotic manipulation,” in Conference on Robot Learning (CoRL) , 2018, pp. 373–385
2018
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C. Wang, D. Xu, Y. Zhu, R. Martín-Martín, C. Lu, L. Fei-Fei, and S. Savarese, “Densefusion: 6D object pose estimation by iterative dense fusion,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2019, pp. 3343–3352
2019
Closest in time.
A. Mousavian, C. Eppner, and D. Fox, “6-DOF GraspNet: Variational grasp generation for object manipulation,” in International Conference on Computer Vision (ICCV) , 2019
2019
Closest in time.
X. Deng, A. Mousavian, Y. Xiang, F. Xia, T. Bretl, and D. Fox, “PoseRBPF: A rao-blackwellized particle filter for 6D object pose tracking,” in Robotics: Science and Systems (RSS) , 2019
2019
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C. Eppner, A. Mousavian, and D. Fox, “A billion ways to grasps - an evaluation of grasp sampling schemes on a dense, physics-based grasp data set,” in Proceedings of the International Symposium on Robotics Research (ISRR) , Hanoi, Vietnam, 2019
2019
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D. Pathak, Y. Shentu, D. Chen, P. Agrawal, T. Darrell, S. Levine, and J. Malik, “Learning instance segmentation by interaction,” in IEEE Conference on Computer Vision and Pattern Recognition Workshops , 2018, pp. 2042–2045
2045
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