FlashAvatar: High-fidelity Head Avatar with Efficient Gaussian Embedding

December 03, 2023 ยท Declared Dead ยท ๐Ÿ› Computer Vision and Pattern Recognition

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Authors Jun Xiang, Xuan Gao, Yudong Guo, Juyong Zhang arXiv ID 2312.02214 Category cs.CV: Computer Vision Cross-listed cs.GR Citations 83 Venue Computer Vision and Pattern Recognition Last Checked 2 months ago
Abstract
We propose FlashAvatar, a novel and lightweight 3D animatable avatar representation that could reconstruct a digital avatar from a short monocular video sequence in minutes and render high-fidelity photo-realistic images at 300FPS on a consumer-grade GPU. To achieve this, we maintain a uniform 3D Gaussian field embedded in the surface of a parametric face model and learn extra spatial offset to model non-surface regions and subtle facial details. While full use of geometric priors can capture high-frequency facial details and preserve exaggerated expressions, proper initialization can help reduce the number of Gaussians, thus enabling super-fast rendering speed. Extensive experimental results demonstrate that FlashAvatar outperforms existing works regarding visual quality and personalized details and is almost an order of magnitude faster in rendering speed. Project page: https://ustc3dv.github.io/FlashAvatar/
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