Disco4D: Disentangled 4D Human Generation and Animation from a Single
  Image
Authors: name: Hui En Pang, name: Shuai Liu, name: Zhongang Cai, name: Lei Yang, name: Tianwei Zhang, name: Ziwei Liu

We present Disco4D, a novel Gaussian Splatting framework for 4D
human generation and animation from a single image. Different from existing
methods, Disco4D distinctively disentangles clothings (with Gaussian models)
from the human body (with SMPL-X model), significantly enhancing the generation
details and flexibility. It has the following technical innovations.
1) Disco4D learns to efficiently fit the clothing Gaussians over the
SMPL-X Gaussians. 2) It adopts diffusion models to enhance the 3D
generation process, e.g., modeling occluded parts not visible in the
input image. 3) It learns an identity encoding for each clothing
Gaussian to facilitate the separation and extraction of clothing assets.
Furthermore, Disco4D naturally supports 4D human animation with vivid dynamics.
Extensive experiments demonstrate the superiority of Disco4D on 4D human
generation and animation tasks. Our visualizations can be found in
https://disco-4d.github.io/.