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dc.contributor.authorVyas, Bharaten_US
dc.contributor.authorO'Sullivan, Carolen_US
dc.contributor.editorLiu, Lingjieen_US
dc.contributor.editorAverkiou, Melinosen_US
dc.date.accessioned2024-04-16T15:29:27Z
dc.date.available2024-04-16T15:29:27Z
dc.date.issued2024
dc.identifier.isbn978-3-03868-239-4
dc.identifier.issn1017-4656
dc.identifier.urihttps://doi.org/10.2312/egp.20241042
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egp20241042
dc.description.abstractComputer animation of realistic human characters remains a significant challenge. This work used deep reinforcement learning to generate physics-based characters with diverse body shapes. We aimed to replicate reference motions like walking or jogging while considering individual variations in body shape and mass. Reference motions served as training targets, accounting for differences in shape parameters to accommodate mass variations. This method produced animations that accurately capture human motion details, leading to diverse and lifelike character performances.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Physical simulation; Procedural animation; Motion capture
dc.subjectComputing methodologies → Physical simulation
dc.subjectProcedural animation
dc.subjectMotion capture
dc.titleShapeVerse: Physics-based Characters with Varied Body Shapesen_US
dc.description.seriesinformationEurographics 2024 - Posters
dc.description.sectionheadersPosters
dc.identifier.doi10.2312/egp.20241042
dc.identifier.pages2 pages


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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License