Neural radiance field (NeRF) has become a popular 3D representation method for human avatar reconstruction due to its high-quality rendering capabilities, e.g., regarding novel views and poses. However, previous methods for editing the geometry and appearance of the avatar only allow for global editing through body shape parameters and 2D texture maps. In this paper, we propose a new approach named \textbf{U}nified \textbf{V}olumetric \textbf{A}vatar (\textbf{UVA}) that enables local and independent editing of both geometry and texture, while retaining the ability to render novel views and poses. UVA transforms each observation point to a canonical space using a skinning motion field and represents geometry and texture in separate neural fields. Each field is composed of a set of structured latent codes that are attached to anchor nodes on a deformable mesh in canonical space and diffused into the entire space via interpolation, allowing for local editing. To address spatial ambiguity in code interpolation, we use a local signed height indicator. We also replace the view-dependent radiance color with a pose-dependent shading factor to better represent surface illumination in different poses. Experiments on multiple human avatars demonstrate that our UVA achieves competitive results in novel view synthesis and novel pose rendering while enabling local and independent editing of geometry and appearance. The source code will be released.

翻译：神经辐射场（NeRF）凭借其高质量渲染能力（如新视角和新姿态渲染），已成为人体虚拟化身重建中流行的三维表示方法。然而，以往编辑化身几何与外观的方法仅能通过人体形状参数和二维纹理图进行全局编辑。本文提出一种名为统一化体积化虚拟化身（UVA）的新方法，在保持新视角和新姿态渲染能力的同时，能对几何与纹理进行局部独立编辑。UVA通过蒙皮运动场将每个观测点变换至规范空间，并在独立神经场中分别表示几何与纹理。每个场由一组结构化隐编码构成，这些编码附着于规范空间可变形网格上的锚节点，并通过插值扩散至整个空间，从而实现局部编辑。为解决编码插值中的空间模糊性问题，我们采用局部符号高度指示器。同时，我们引入姿态相关着色因子替代视角相关辐射颜色，以更准确地表示不同姿态下的表面光照。多个人体虚拟化身的实验表明，UVA在新视角合成与新姿态渲染中取得具有竞争力的结果，并支持几何与外观的局部独立编辑。源代码将公开发布。