  We present SplatFace, a novel Gaussian splatting framework designed for 3D
human face reconstruction without reliance on accurate pre-determined geometry.
Our method is designed to simultaneously deliver both high-quality novel view
rendering and accurate 3D mesh reconstructions. We incorporate a generic 3D
Morphable Model (3DMM) to provide a surface geometric structure, making it
possible to reconstruct faces with a limited set of input images. We introduce
a joint optimization strategy that refines both the Gaussians and the morphable
surface through a synergistic non-rigid alignment process. A novel distance
metric, splat-to-surface, is proposed to improve alignment by considering both
the Gaussian position and covariance. The surface information is also utilized
to incorporate a world-space densification process, resulting in superior
reconstruction quality. Our experimental analysis demonstrates that the
proposed method is competitive with both other Gaussian splatting techniques in
novel view synthesis and other 3D reconstruction methods in producing 3D face
meshes with high geometric precision.
