GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts-Reference-Cited by-同舟云学术

GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts

Published:2023-06 Issue: Volume: Page:
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Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Geng Haoran¹,Xu Helin²,Zhao Chengyang¹,Xu Chao³,Yi Li²,Huang Siyuan⁴,Wang He¹

Affiliation:

1. Peking University,CFCS

2. Tsinghua University

3. University of California,Los Angeles

4. Beijing Institute for General Artificial Intelligence

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203924.pdf?arnumber=10203924

Reference72 articles.

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3. Unsupervised domain adaptation by backpropagation;ganin;International Conference on Machine Learning,0

5. ARNOLD: A benchmark for language-grounded task learning with continuous states in realistic scenes;gong;Workshop on Language and Robotics at CoRL 2022,0

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