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Relightable 3D Avatar Reconstruction with Semantic-Adaptive Motion-Illumination Responses — arXiv:2609.24158

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.24158
License (as archived): CC0-1.0
Archived: 2026-10-09T22:05:14.402Z
SHA-256 of the archived text: 049478728c2bb5beac299d2addb0c9fb4c6db01234ebbecbf829544aabb0308c
Stable URL of this page: https://metraipolis.com/documento/dc_f87e73dc47be

How to cite

Relightable 3D Avatar Reconstruction with Semantic-Adaptive Motion-Illumination Responses — arXiv:2609.24158 — arXiv (en), https://arxiv.org/abs/2609.24158 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_f87e73dc47be (Metraipolis archive dc_f87e73dc47be, sha256 049478728c2bb5beac299d2addb0c9fb4c6db01234ebbecbf829544aabb0308c)

BibTeX

@misc{dcf87e73dc47be,
  title = {Relightable 3D Avatar Reconstruction with Semantic-Adaptive Motion-Illumination Responses — arXiv:2609.24158},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.24158},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_f87e73dc47be; sha256 049478728c2bb5beac299d2addb0c9fb4c6db01234ebbecbf829544aabb0308c},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.24158. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

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 plausibility. To address this limitation, we propose SAMIRA, a 3D Gaussian avatar framework for semantic-adaptive motion-illumination response modeling. For motion response modeling, the Semantic-Adaptive Motion Response module rasterizes current-to-reference mesh displacements into a topology-consistent UV space and leverages facial semantics to route displacement features through semantic-specific modulators, predicting localized Gaussian geometric residuals beyond coarse mesh binding. For illumination response modeling, the Semantic-Adaptive Illumination Response module learns compact diffuse and specular response factors for each facial region, allowing Gaussians in different regions to adapt their illumination responses to novel environment lighting. These response factors are incorporated into deferred physically based shading, providing a lightweight approximation of semantic-dependent illumination effects. Extensive experiments on self-reenactment, cross-reenactment, and relighting demonstrate that SAMIRA improves both fine-grained expression reconstruction and relighting realism over existing methods.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-22 in cs.CV).
Categorie arXiv: Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2609.24158 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-09T21:45:20.998Z dalla pagina https://arxiv.org/catchup/cs.CV/2026-09-22?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).