Wang, Yi, Ma, Jian, Shao, Ruizhi, Feng, Qiao, Lai, Yukun  ORCID: https://orcid.org/0000-0002-2094-5680 and Li, Kun
2024.
HumanCoser: Layered 3D human generation via semantic-aware diffusion model.
Presented at: IEEE International Symposium on Mixed and Augmented Reality (ISMAR),
Bellevue, WA, USA,
21-25 October 2024.
Proceedings of International Symposium on Mixed and Augmented Reality.
IEEE,
pp. 436-445.
10.1109/ISMAR62088.2024.00058
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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 partlevel 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-ofthe- art layered 3D human generation with complex clothing but also supports virtual try-on and layered human animation. More results and the code can be found on our project page at https: //cic.tju.edu.cn/faculty/likun/projects/HumanCoser.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Date Type: | Published Online |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Publisher: | IEEE |
| ISBN: | 979-8-3315-1648-2 |
| ISSN: | 1554-7868 |
| Date of First Compliant Deposit: | 7 September 2024 |
| Date of Acceptance: | 31 July 2024 |
| Last Modified: | 22 Jan 2025 10:40 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/171912 |
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