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Conditional motion in-betweening

Cited 5 time in Web of Science Cited 10 time in Scopus
Authors

Kim, Jihoon; Byun, Taehyun; Shin, Seungyoun; Won, Jungdam; Choi, Sungjoon

Issue Date
2022-12
Publisher
Pergamon Press
Citation
Pattern Recognition, Vol.132, p. 108894
Abstract
Motion in-betweening (MIB) is a process of generating intermediate skeletal movement between the given start and target poses while preserving the naturalness of the motion, such as periodic footstep motion while walking. Although state-of-the-art MIB methods are capable of producing plausible mo-tions given sparse key-poses, they often lack the controllability to generate motions satisfying the se-mantic contexts required in practical applications. We focus on the method that can handle pose or se-mantic conditioned MIB tasks using a unified model. We also present a motion augmentation method to improve the quality of pose-conditioned motion generation via defining a distribution over smooth tra-jectories. Our proposed method outperforms the existing state-of-the-art MIB method in pose prediction errors while providing additional controllability. Our code and results are available on our project web page: https://jihoonerd.github.io/Conditional- Motion- In- Betweening . (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
ISSN
0031-3203
URI
https://hdl.handle.net/10371/201170
DOI
https://doi.org/10.1016/j.patcog.2022.108894
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