Long-term Motion In-betweening via Keyframe Prediction

dc.contributor.authorHong, Seokhyeonen_US
dc.contributor.authorKim, Haeminen_US
dc.contributor.authorCho, Kyungminen_US
dc.contributor.authorNoh, Junyongen_US
dc.contributor.editorSkouras, Melinaen_US
dc.contributor.editorWang, Heen_US
dc.date.accessioned2024-08-20T08:42:22Z
dc.date.available2024-08-20T08:42:22Z
dc.date.issued2024
dc.description.abstractMotion in-betweening has emerged as a promising approach to enhance the efficiency of motion creation due to its flexibility and time performance. However, previous in-betweening methods are limited to generating short transitions due to growing pose ambiguity when the number of missing frames increases. This length-related constraint makes the optimization hard and it further causes another constraint on the target pose, limiting the degrees of freedom for artists to use. In this paper, we introduce a keyframe-driven approach that effectively solves the pose ambiguity problem, allowing robust in-betweening performance on various lengths of missing frames. To incorporate keyframe-driven motion synthesis, we introduce a keyframe score that measures the likelihood of a frame being used as a keyframe as well as an adaptive keyframe selection method that maintains appropriate temporal distances between resulting keyframes. Additionally, we employ phase manifolds to further resolve the pose ambiguity and incorporate trajectory conditions to guide the approximate movement of the character. Comprehensive evaluations, encompassing both quantitative and qualitative analyses, were conducted to compare our method with state-of-theart in-betweening approaches across various transition lengths. The code for the paper is available at https://github. com/seokhyeonhong/long-miben_US
dc.description.number8
dc.description.sectionheadersCharacter Animation I: Synthesis and Capture
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume43
dc.identifier.doi10.1111/cgf.15171
dc.identifier.issn1467-8659
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.15171
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15171
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies → Animation
dc.subjectComputing methodologies → Animation
dc.titleLong-term Motion In-betweening via Keyframe Predictionen_US
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