  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.
