H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions-Reference-Cited by-同舟云学术

H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions

Published:2023-05-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Robotics and Automation (ICRA)
language:
Short-container-title:

Author:

Ota Kei¹,Tung Hsiao-Yu²,Smith Kevin A.²,Cherian Anoop³,Marks Tim K.³,Sullivan Alan³,Kanezaki Asako⁴,Tenenbaum Joshua B.²

Affiliation:

1. Information Technology R&D Center, Mitsubishi Electric Corporation,Japan

2. Massachusetts Institute of Technology,Department of Brain and Cognitive Sciences,Cambridge,MA,USA

3. Mitsubishi Electric Research Labs,Cambridge,MA,USA

4. Tokyo Institute of Technology,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160575.pdf?arnumber=10160575

Reference32 articles.

1. Ditto: Building Digital Twins of Articulated Objects from Interaction

2. Shape2Motion: Joint Analysis of Motion Parts and Attributes From 3D Shapes

3. Category-Independent Articulated Object Tracking with Factor Graphs

4. A Probabilistic Framework for Learning Kinematic Models of Articulated Objects

5. CURL: Contrastive unsupervised representations for reinforcement learning;laskin;Proceedings of the 37th International Conference on Machine Learning ser Proceedings of Machine Learning Research,0

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning Interaction Regions and Motion Trajectories Simultaneously From Egocentric Demonstration Videos;IEEE Robotics and Automation Letters;2023-10