Gaussianavatar-Editor: Photorealistic Animatable Gaussian Head Avatar Editor
We introduce GaussianAvatar-Editor, an innovative framework for text-driven editing of animatable Gaussian head avatars that can be fully controlled in expression, pose, and viewpoint. Unlike static 3D Gaussian editing, editing animatable 4D Gaussian avatars presents challenges related to motion occlusion and spatial-temporal inconsistency. To address these issues, we propose the Weighted Alpha Blending Equation (WABE). This function enhances the blending weight of visible Gaussians while suppressing the influence on non-visible Gaussians, effectively handling motion occlusion during editing. Furthermore, to improve editing quality and ensure 4D consistency, we incorporate conditional adversarial learning into the editing process. This strategy helps to refine the edited results and maintain consistency throughout the animation. By integrating these methods, our GaussianAvatar-Editor
Authors
- Xiangyue Liu (ORCID: https://orcid.org/0000-0003-4463-8068)
- Ping Tan (ORCID: https://orcid.org/0000-0002-4506-6973)
- Heng Li (ORCID: https://orcid.org/0000-0002-3187-9041)
- Qi Zhang (ORCID: https://orcid.org/0009-0002-9776-4658)
- Li Yi (ORCID: https://orcid.org/0000-0002-7547-5073)
- Yuan Liu (ORCID: https://orcid.org/0000-0002-1361-0882)
- Kunming Luo (ORCID: https://orcid.org/0000-0002-5070-7392)
Institutions
- Hong Kong University of Science and Technology (HK)
- Tencent (China) (CN)
- Tsinghua University (CN)
Publication Details
- Published
- 2025-03-25
- DOI
- https://doi.org/10.1109/3dv66043.2025.00108
- Primary Topic
- Augmented Reality Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00