노이즈 기반 아바타 지오메트리 생성과 가우시안 스플래팅 시각화

sa (a) Points (b) Depth/Color (c) Normal (d) Mesh 𝐗𝐗 ~𝒩𝒩 Figure 1. Our generative framework produces diverse avatar geometry sequences from noise, with geometries represented as points (a). For visualization, these points can be rendered via Gaussian splatting (GS), producing depth images (b) and normal images (c). Colors (b) can then be obtained by GS optimization, using a depth-guided video generation model (Wan 2.1), while the normal images (c) effectively highlight fine folds and wrinkles. Our synthesized geometries are of high quality and can be directly converted into meshes (d) via Poisson reconstruction. The highlighted regions demonstrate fine-grained garment dynamics that faithfully follow human motion.