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Learning a shared deformation space for efficient design-preserving garment transfer

文献类型：期刊论文

作者Shi, Min4; Wei, Yukun4; Chen, Lan2,3; Zhu, Dengming1; Mao, Tianlu1; Wang, Zhaoqi1
刊名GRAPHICAL MODELS
出版日期2021-05-01
卷号115页码:12
ISSN号1524-0703
关键词Garment transfer Cloth deformation Shape analysis
DOI10.1016/j.gmod.2021.101106
英文摘要Garment transfer from a source mannequin to a shape-varying individual is a vital technique in computer graphics. Existing garment transfer methods are either time consuming or lack designed details especially for clothing with complex styles. In this paper, we propose a data-driven approach to efficiently transfer garments between two distinctive bodies while preserving the source design. Given two sets of simulated garments on a source body and a target body, we utilize the deformation gradients as the representation. Since garments in our dataset are with various topologies, we embed cloth deformation to the body. For garment transfer, the deformation is decomposed into two aspects, typically style and shape. An encoder-decoder network is proposed to learn a shared space which is invariant to garment style but related to the deformation of human bodies. For a new garment in a different style worn by the source human, our method can efficiently transfer it to the target body with the shared shape deformation, meanwhile preserving the designed details. We qualitatively and quantitatively evaluate our method on a diverse set of 3D garments that showcase rich wrinkling patterns. Experiments show that the transferred garments can preserve the source design even if the target body is quite different from the source one.
资助项目National Natural Science Foundation of China[61972379]
WOS研究方向Computer Science
语种英语
出版者ACADEMIC PRESS INC ELSEVIER SCIENCE
WOS记录号WOS:000654031100002
源URL[http://119.78.100.204/handle/2XEOYT63/17542]  
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.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
4.North China Elect Power Univ, Sch Control & Comp Engn, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Shi, Min,Wei, Yukun,Chen, Lan,et al. Learning a shared deformation space for efficient design-preserving garment transfer[J]. GRAPHICAL MODELS,2021,115:12.
APA Shi, Min,Wei, Yukun,Chen, Lan,Zhu, Dengming,Mao, Tianlu,&Wang, Zhaoqi.(2021).Learning a shared deformation space for efficient design-preserving garment transfer.GRAPHICAL MODELS,115,12.
MLA Shi, Min,et al."Learning a shared deformation space for efficient design-preserving garment transfer".GRAPHICAL MODELS 115(2021):12.

入库方式： OAI收割

来源：计算技术研究所

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