Implicit Shape Avatar Generalization across Pose and Identity

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dc.contributor.authorLoranchet, Guillaumeen_US
dc.contributor.authorHellier, Pierreen_US
dc.contributor.authorSchnitzler, Francoisen_US
dc.contributor.authorBoukhayma, Adnaneen_US
dc.contributor.authorRegateiro, Joaoen_US
dc.contributor.authorMulton, Francken_US
dc.contributor.editorCeylan, Duyguen_US
dc.contributor.editorLi, Tzu-Maoen_US
dc.date.accessioned2025-05-09T09:36:31Z
dc.date.available2025-05-09T09:36:31Z
dc.date.issued2025
dc.description.abstractThe creation of realistic animated avatars has become a hot-topic in both academia and the creative industry. Recent advancements in deep learning and implicit representations have opened new research avenues, particularly in enhancing avatar details with lightweight models. This paper introduces an improvement over the state-of-the-art implicit Fast-SNARF method to permit generalization to novel motions and shape identities. Fast-SNARF trains two networks: an occupancy network to predict the shape of a character in canonical space, and a Linear Blend Skinning network to deform it into arbitrary poses. However, it requires a separated model for each subject. We extend this work by conditioning both networks on an identity parameter, enabling a single model to generalize across multiple identities, without increasing the model's size, compared to Fast-SNARF.en_US
dc.description.sectionheadersShort Paper 4
dc.description.seriesinformationEurographics 2025 - Short Papers
dc.identifier.doi10.2312/egs.20251049
dc.identifier.isbn978-3-03868-268-4
dc.identifier.issn1017-4656
dc.identifier.pages4 pages
dc.identifier.urihttps://doi.org/10.2312/egs.20251049
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/egs20251049
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 → Motion processing; Mesh models
dc.subjectComputing methodologies → Motion processing
dc.subjectMesh models
dc.titleImplicit Shape Avatar Generalization across Pose and Identityen_US
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