3D Gaussian Blendshapes for Head Avatar Animation

Fuente: arXiv
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Autori principali: Ma, Shengjie, Weng, Yanlin, Shao, Tianjia, Zhou, Kun
Natura: Preprint
Pubblicazione: 2024
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author Ma, Shengjie
Weng, Yanlin
Shao, Tianjia
Zhou, Kun
author_facet Ma, Shengjie
Weng, Yanlin
Shao, Tianjia
Zhou, Kun
contents We introduce 3D Gaussian blendshapes for modeling photorealistic head avatars. Taking a monocular video as input, we learn a base head model of neutral expression, along with a group of expression blendshapes, each of which corresponds to a basis expression in classical parametric face models. Both the neutral model and expression blendshapes are represented as 3D Gaussians, which contain a few properties to depict the avatar appearance. The avatar model of an arbitrary expression can be effectively generated by combining the neutral model and expression blendshapes through linear blending of Gaussians with the expression coefficients. High-fidelity head avatar animations can be synthesized in real time using Gaussian splatting. Compared to state-of-the-art methods, our Gaussian blendshape representation better captures high-frequency details exhibited in input video, and achieves superior rendering performance.
format Preprint
id arxiv_https___arxiv_org_abs_2404_19398
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle 3D Gaussian Blendshapes for Head Avatar Animation
Ma, Shengjie
Weng, Yanlin
Shao, Tianjia
Zhou, Kun
Graphics
Computer Vision and Pattern Recognition
We introduce 3D Gaussian blendshapes for modeling photorealistic head avatars. Taking a monocular video as input, we learn a base head model of neutral expression, along with a group of expression blendshapes, each of which corresponds to a basis expression in classical parametric face models. Both the neutral model and expression blendshapes are represented as 3D Gaussians, which contain a few properties to depict the avatar appearance. The avatar model of an arbitrary expression can be effectively generated by combining the neutral model and expression blendshapes through linear blending of Gaussians with the expression coefficients. High-fidelity head avatar animations can be synthesized in real time using Gaussian splatting. Compared to state-of-the-art methods, our Gaussian blendshape representation better captures high-frequency details exhibited in input video, and achieves superior rendering performance.
title 3D Gaussian Blendshapes for Head Avatar Animation
topic Graphics
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2404.19398