- [2024/11] GaussianStyle is accepted by 3DV 2025.
3DV 2025
GaussianStyle: Gaussian Head Avatar via StyleGAN
Pinxin Liu*,
Luchuan Song*,
Daoan Zhang,
Hang Hua,
Yunlong Tang,
Huaijin Tu,
Jiebo Luo,
Chenliang Xu
(*Equal Contribution)
Existing methods like Neural Radiation Fields (NeRF) and 3D Gaussian Splatting (3DGS) have made significant strides in facial attribute control such as facial animation and components editing, yet they struggle with fine-grained representation and scalability in dynamic head modeling. To address these limitations, we propose GaussianStyle, a novel framework that integrates the volumetric strengths of 3DGS with the powerful implicit representation of StyleGAN. The GaussianStyle preserves structural information, such as expressions and poses, using Gaussian points, while projecting the implicit volumetric representation into StyleGAN to capture high-frequency details and mitigate the over-smoothing commonly observed in neural texture rendering. Experimental outcomes indicate that our method achieves state-of-the-art performance in reenactment, novel view synthesis, and animation.
The website is inspired by the template of AI4Animation.
This project is only for research or education purposes, and not freely available for commercial use or redistribution. The motion capture data is available only under the terms of the Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.