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Conditional motion in-betweening
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DOI：10.1016/j.patcog.2022.108894.png)
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Abstract
En 中文
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/ )
Keywords:
Motion in-betweening
Conditional motion generation
Generative model
Motion data augmentation
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