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Understanding the continuous states of objects is essential for task learning and planning in the real world.
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2021
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2021
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2021
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V. Makoviychuk, L. Wawrzyniak, Y. Guo, M. Lu, K. Storey, M. Macklin, D. Hoeller, N. Rudin, A. Allshire, A. Handa
2021
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2021
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2021
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A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark
2021
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2022
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C. Li, R. Zhang, J. Wong, C. Gokmen, S. Srivastava, R. Martín-Martín, C. Wang, G. Levine, M. Lingelbach, J. Sun
2022
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2022
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2022
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2022
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2022
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2022
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2022
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2022
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C. Saharia, W. Chan, S. Saxena, L. Li, J. Whang, E. Denton, S. K. S. Ghasemipour, B. K. Ayan, S. S. Mahdavi, R. G. Lopes
2022
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M. Shridhar, L. Manuelli, and D. Fox, “CLIPort: What and where pathways for robotic manipulation,” in
2022
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2022
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S. Srivastava, C. Li, M. Lingelbach, R. Martín-Martín, F. Xia, K. E. Vainio, Z. Lian, C. Gokmen, S. Buch, K. Liu
2022
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W.-C. Tseng, H.-J. Liao, L. Yen-Chen, and M. Sun, “CLA-NeRF: Category-level articulated neural radiance field,” in
2022
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2022
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F. Wei, R. Chabra, L. Ma, C. Lassner, M. Zollhoefer, S. Rusinkiewicz, C. Sweeney, R. Newcombe, and M. Slavcheva, “Self-supervised neural articulated shape and appearance models,” in
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K. Zheng, X. Chen, O. C. Jenkins, and X. E. Wang, “VLMbench: A compositional benchmark for vision-and-language manipulation,”
2022
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2023
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H. Geng, Z. Li, Y. Geng, J. Chen, H. Dong, and H. Wang, “PartManip: Learning cross-category generalizable part manipulation policy from point cloud observations,” in
2023
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2023
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J. Gu, F. Xiang, X. Li, Z. Ling, X. Liu, T. Mu, Y. Tang, S. Tao, X. Wei, Y. Yao
2023
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S. Huang, Z. Wang, P. Li, B. Jia, T. Liu, Y. Zhu, W. Liang, and S.-C. Zhu, “Diffusion-based generation, optimization, and planning in 3D scenes,” in
2023
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L. Ma, J. Meng, S. Liu, W. Chen, J. Xu, and R. Chen, “Sim2Real
2023
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M. Mittal, C. Yu, Q. Yu, J. Liu, N. Rudin, D. Hoeller, J. L. Yuan, P. P. Tehrani, R. Singh, Y. Guo
2023
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