Automatic temporal clothing deformation prediction: applicable to variable shape and motion

doi:10.1177/00405175231178049

	Automatic temporal clothing deformation prediction: applicable to variable shape and motion
	Shi, Min 1,4; Zhuo, Xinru 1; Mao, Tianlu 2; Zhu, Dengming 2; Shao, Xinyan 3
	2023-06-23
发表期刊	TEXTILE RESEARCH JOURNAL
ISSN	0040-5175
页码	16
摘要	Simulating temporal three-dimensional (3D) deformations of clothing worn by the human body is a core technology in computer graphics that plays a vital role in various fields, such as computer games, animation, and movies. Physics-based simulation and data-driven methods are two mainstream technologies used to generate clothing deformation. However, when it is necessary to quickly generate clothing animations of different body shapes and motions, the existing methods cannot balance efficiency and effectiveness. In this paper, we present a learning-based method, given human body shape and motion, which automatically synthesizes temporal 3D deformations of clothing in real-time. A temporal framework based on the transformer is designed to capture the correlation between clothing deformation and shape features of the moving human body, as well as the frame-level dependency. A feature fusion strategy is an innovation used to fuse the two features of shape and motion. We also perform post-processing on the penetration of clothing and the human body, generating collision-free cloth deformation sequences. To evaluate the method, we build a human motion dataset based on the large-scale public human body dataset AMASS, and further develop a clothing deformation dataset. We qualitatively and quantitatively demonstrate that our approach outperforms existing methods in terms of temporal clothing deformation with variable shape and motion, as well as producing realistic deformation at interactive rates.
关键词	Clothing simulation deep learning computer graphics transformer
DOI	10.1177/00405175231178049
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61972379]
WOS研究方向	Materials Science
WOS类目	Materials Science, Textiles
WOS记录号	WOS:001014554200001
出版者	SAGE PUBLICATIONS LTD
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/21236
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, Min
作者单位	1.North China Elect Power Univ, Sch Control & Comp Engn, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 3.Beijing Inst Fash Technol, Beijing, Peoples R China 4.North China Elect Power, Beijing 102206, Peoples R China
推荐引用方式 GB/T 7714	Shi, Min,Zhuo, Xinru,Mao, Tianlu,et al. Automatic temporal clothing deformation prediction: applicable to variable shape and motion[J]. TEXTILE RESEARCH JOURNAL,2023:16.
APA	Shi, Min,Zhuo, Xinru,Mao, Tianlu,Zhu, Dengming,&Shao, Xinyan.(2023).Automatic temporal clothing deformation prediction: applicable to variable shape and motion.TEXTILE RESEARCH JOURNAL,16.
MLA	Shi, Min,et al."Automatic temporal clothing deformation prediction: applicable to variable shape and motion".TEXTILE RESEARCH JOURNAL (2023):16.