ACE: Adversarial Correspondence Embedding for Cross Morphology Motion Retargeting from Human to Nonhuman Characters-Reference-Cited by-同舟云学术

ACE: Adversarial Correspondence Embedding for Cross Morphology Motion Retargeting from Human to Nonhuman Characters

Published:2023-12-10 Issue: Volume: Page:
ISSN:
Container-title:SIGGRAPH Asia 2023 Conference Papers
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Author:

Li Tianyu¹^ORCID,Won Jungdam²^ORCID,Clegg Alexander³^ORCID,Kim Jeonghwan¹^ORCID,Rai Akshara³^ORCID,Ha Sehoon¹^ORCID

Affiliation:

1. Georgia Institute of Technology, United States of America

2. Seoul National University, South Korea

3. Meta, United States of America

Funder

Meta

NSF: FW-HTF-P: Reshaping Construction Work Conventions: Endowing Collaborative Construction Robots with Social Intelligence for Contextually-Appropriate Robot Behaviors

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3610548.3618255

Reference45 articles.

1. Michel Abdul-Massih, Innfarn Yoo, and Bedrich Benes. 2017. Motion style retargeting to characters with different morphologies. In Computer Graphics Forum, Vol. 36. Wiley Online Library, 86–99.

2. Skeleton-aware networks for deep motion retargeting

3. Noam Aigerman, Kunal Gupta, Vladimir G Kim, Siddhartha Chaudhuri, Jun Saito, and Thibault Groueix. 2022. Neural jacobian fields: Learning intrinsic mappings of arbitrary meshes. arXiv preprint arXiv:2205.02904 (2022).

4. Blizzard. 2016. Overwatch. https://overwatch.blizzard.com/

5. BostonDynamics. 2019. Spot® - The Agile Mobile Robot. https://www.bostondynamics.com/products/spot

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