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Relightable 3D Avatar Reconstruction with Semantic-Adaptive Motion-Illumination Responses

arXiv · AI, language, vision and robotics · article · Sep 21, 2026 · UTC

Reconstructing expressive and relightable 3D head avatars from monocular videos remains challenging in computer vision, as it requires accurate modeling of both non-rigid facial motion and illumination-dependent appearance. Existing Gaussian avatar methods commonly rely on globally coupled representations, in which Gaussian primitives share a unified motion or illumination response model. Such uniform modeling neglects the distinct motion patterns and material/reflectance properties of different facial semantic regions, thereby limiting fine-grained animation accuracy and reducing relighting p

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Evidence & attribution

First collected: 2026-09-23T08:01:43.213Z. This is not the publication date.