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HumanCoser: Layered 3D Human Generation via Semantic-Aware Diffusion Model

Authors :
Wang, Yi
Ma, Jian
Shao, Ruizhi
Feng, Qiao
Lai, Yu-kun
Li, Kun
Publication Year :
2024

Abstract

This paper aims to generate physically-layered 3D humans from text prompts. Existing methods either generate 3D clothed humans as a whole or support only tight and simple clothing generation, which limits their applications to virtual try-on and part-level editing. To achieve physically-layered 3D human generation with reusable and complex clothing, we propose a novel layer-wise dressed human representation based on a physically-decoupled diffusion model. Specifically, to achieve layer-wise clothing generation, we propose a dual-representation decoupling framework for generating clothing decoupled from the human body, in conjunction with an innovative multi-layer fusion volume rendering method. To match the clothing with different body shapes, we propose an SMPL-driven implicit field deformation network that enables the free transfer and reuse of clothing. Extensive experiments demonstrate that our approach not only achieves state-of-the-art layered 3D human generation with complex clothing but also supports virtual try-on and layered human animation.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2408.11357
Document Type :
Working Paper