Self-Supervised Humidity-Controllable Garment Simulation via Capillary Bridge Modeling

doi:10.1111/cgf.70236

	Self-Supervised Humidity-Controllable Garment Simulation via Capillary Bridge Modeling
	Shi, M.1; Wang, X.1; Zhang, J.2; Gao, L.3; Zhu, D.3,4; Zhang, H.5
	2025-10-01
发表期刊	COMPUTER GRAPHICS FORUM
ISSN	0167-7055
卷号	44 期号:7 页码:10
摘要	Simulating wet clothing remains a significant challenge due to the complex physical interactions between moist fabric and the human body, compounded by the lack of dedicated datasets for training data-driven models. Existing self-supervised approaches struggle to capture moisture-induced dynamics such as skin adhesion, anisotropic surface resistance, and non-linear wrinkling, leading to limited accuracy and efficiency. To address this, we present SHGS, a novel self-supervised framework for humidity-controllable clothing simulation grounded in the physical modeling of capillary bridges that form between fabric and skin. We abstract the forces induced by wetness into two physically motivated components: a normal adhesive force derived from Laplace pressure and a tangential shear-resistance force that opposes relative motion along the fabric surface. By formulating these forces as potential energy for conservative effects and as mechanical work for non-conservative effects, we construct a physics-consistent wetness loss. This enables self-supervised training without requiring labeled data of wet clothing. Our humidity-sensitive dynamics are driven by a multi-layer graph neural network, which facilitates a smooth and physically realistic transition between different moisture levels. This architecture decouples the garment's dynamics in wet and dry states through a local weight interpolation mechanism, adjusting the fabric's behavior in response to varying humidity conditions. Experiments demonstrate that SHGS outperforms existing methods in both visual fidelity and computational efficiency, marking a significant advancement in realistic wet-cloth simulation.
关键词	CCS Concepts center dot Computing methodologies -> Animation
DOI	10.1111/cgf.70236
收录类别	SCI
语种	英语
资助项目	Suzhou Science and Technology Program
WOS研究方向	Computer Science
WOS类目	Computer Science, Software Engineering
WOS记录号	WOS:001590874700001
出版者	WILEY
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/41679
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Shi, M.
作者单位	1.North China Elect Power Univ, Sch Control & Comp Engn, Baoding, Peoples R China 2.Beihang Univ, State Key Lab Virtual Real Technol & Syst, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 4.Taicang ZK Inst Informat & Technol, Taicang, Peoples R China 5.Beijing Inst Fash Technol, Sch Mat Design & Engn, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Shi, M.,Wang, X.,Zhang, J.,et al. Self-Supervised Humidity-Controllable Garment Simulation via Capillary Bridge Modeling[J]. COMPUTER GRAPHICS FORUM,2025,44(7):10.
APA	Shi, M.,Wang, X.,Zhang, J.,Gao, L.,Zhu, D.,&Zhang, H..(2025).Self-Supervised Humidity-Controllable Garment Simulation via Capillary Bridge Modeling.COMPUTER GRAPHICS FORUM,44(7),10.
MLA	Shi, M.,et al."Self-Supervised Humidity-Controllable Garment Simulation via Capillary Bridge Modeling".COMPUTER GRAPHICS FORUM 44.7(2025):10.