GART: Gaussian Articulated Template Models
Jiahui Lei Yufu Wang Georgios Pavlakos Lingjie Liu Kostas Daniilidis
We introduce Gaussian Articulated Template Model GART, an explicit,
efficient, and expressive representation for non-rigid articulated subject
capturing and rendering from monocular videos. GART utilizes a mixture of
moving 3D Gaussians to explicitly approximate a deformable subject's geometry
and appearance. It takes advantage of a categorical template model prior (SMPL,
SMAL, etc.) with learnable forward skinning while further generalizing to more
complex non-rigid deformations with novel latent bones. GART can be
reconstructed via differentiable rendering from monocular videos in seconds or
minutes and rendered in novel poses faster than 150fps.