B2F: End-to-End Body-to-Face Motion Generation with Style Reference

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dc.contributor.authorJang, Bokyungen_US
dc.contributor.authorJung, Eunhoen_US
dc.contributor.authorLee, Yoonsangen_US
dc.contributor.editorChristie, Marcen_US
dc.contributor.editorHan, Ping-Hsuanen_US
dc.contributor.editorLin, Shih-Syunen_US
dc.contributor.editorPietroni, Nicoen_US
dc.contributor.editorSchneider, Teseoen_US
dc.contributor.editorTsai, Hsin-Rueyen_US
dc.contributor.editorWang, Yu-Shuenen_US
dc.contributor.editorZhang, Eugeneen_US
dc.date.accessioned2025-10-07T06:02:19Z
dc.date.available2025-10-07T06:02:19Z
dc.date.issued2025
dc.description.abstractHuman motion naturally integrates body movements and facial expressions, forming a unified perception. If a virtual character's facial expression does not align well with its body movements, it may weaken the perception of the character as a cohesive whole. Motivated by this, we propose B2F, a model that generates facial motions aligned with body movements. B2F takes a facial style reference as input, generating facial animations that reflect the provided style while maintaining consistency with the associated body motion. To achieve this, B2F learns a disentangled representation of content and style, using alignment and consistency-based objectives. We represent style using discrete latent codes learned via the Gumbel-Softmax trick, enabling diverse expression generation with a structured latent representation. B2F outputs facial motion in the FLAME format, making it compatible with SMPL-X characters, and supports ARKit-style avatars through a dedicated conversion module. Our evaluations show that B2F generates expressive and engaging facial animations that synchronize with body movements and style intent, while mitigating perceptual dissonance from mismatched cues, and generalizing across diverse characters and styles.en_US
dc.description.sectionheadersCharacter Animation
dc.description.seriesinformationPacific Graphics Conference Papers, Posters, and Demos
dc.identifier.doi10.2312/pg.20251256
dc.identifier.isbn978-3-03868-295-0
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.2312/pg.20251256
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/pg20251256
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleB2F: End-to-End Body-to-Face Motion Generation with Style Referenceen_US
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