PMP: Learning to Physically Interact with Environments using Part-wise Motion Priors-Reference-Cited by-同舟云学术

PMP: Learning to Physically Interact with Environments using Part-wise Motion Priors

Published:2023-07-23 Issue: Volume: Page:
ISSN:
Container-title:Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Proceedings
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Author:

Bae Jinseok¹^ORCID,Won Jungdam¹^ORCID,Lim Donggeun¹^ORCID,Min Cheol-Hui¹^ORCID,Kim Young Min¹^ORCID

Affiliation:

1. Seoul National University, South Korea

Funder

the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT)

the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program

Publisher

ACM

Reference42 articles.

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5. Anindita Ghosh , Rishabh Dabral , Vladislav Golyanik , Christian Theobalt , and Philipp Slusallek . 2022. IMoS: Intent-Driven Full-Body Motion Synthesis for Human-Object Interactions. arXiv preprint arXiv:2212.07555 ( 2022 ). Anindita Ghosh, Rishabh Dabral, Vladislav Golyanik, Christian Theobalt, and Philipp Slusallek. 2022. IMoS: Intent-Driven Full-Body Motion Synthesis for Human-Object Interactions. arXiv preprint arXiv:2212.07555 (2022).

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