HumanCoser: Layered 3D Human Generation via Semantic-Aware Diffusion Model
<|reference_start|>HumanCoser: Layered 3D Human Generation via Semantic-Aware Diffusion Model: 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.<|reference_end|>
@article{wang2024humancoser:,
    title={HumanCoser: Layered 3D Human Generation via Semantic-Aware Diffusion
  Model},
    author={Yi Wang, Jian Ma, Ruizhi Shao, Qiao Feng, Yu-kun Lai, Kun Li},
    journal={arXiv preprint arXiv:2408.11357},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.11357},
    primaryClass={cs.CV}
}