  Creating relightable and animatable avatars from multi-view or monocular
videos is a challenging task for digital human creation and virtual reality
applications. Previous methods rely on neural radiance fields or ray tracing,
resulting in slow training and rendering processes. By utilizing Gaussian
Splatting, we propose a simple and efficient method to decouple body materials
and lighting from sparse-view or monocular avatar videos, so that the avatar
can be rendered simultaneously under novel viewpoints, poses, and lightings at
interactive frame rates (6.9 fps). Specifically, we first obtain the canonical
body mesh using a signed distance function and assign attributes to each mesh
vertex. The Gaussians in the canonical space then interpolate from nearby body
mesh vertices to obtain the attributes. We subsequently deform the Gaussians to
the posed space using forward skinning, and combine the learnable environment
light with the Gaussian attributes for shading computation. To achieve fast
shadow modeling, we rasterize the posed body mesh from dense viewpoints to
obtain the visibility. Our approach is not only simple but also fast enough to
allow interactive rendering of avatar animation under environmental light
changes. Experiments demonstrate that, compared to previous works, our method
can render higher quality results at a faster speed on both synthetic and real
datasets.
