期刊
COMPUTER GRAPHICS FORUM
卷 38, 期 2, 页码 355-366出版社
WILEY
DOI: 10.1111/cgf.13643
关键词
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资金
- Predoctoral Training Programme of the Department of Education of the Basque Government [PRE_2018_1_0307]
- Marie Curie Individual Fellowship [707326]
- European Research Council [772738 TouchDesign]
- Marie Curie Actions (MSCA) [707326] Funding Source: Marie Curie Actions (MSCA)
This paper presents a learning-based clothing animation method for highly efficient virtual try-on simulation. Given a garment, we preprocess a rich database of physically-based dressed character simulations, for multiple body shapes and animations. Then, using this database, we train a learning-based model of cloth drape and wrinkles, as a function of body shape and dynamics. We propose a model that separates global garment fit, due to body shape, from local garment wrinkles, due to both pose dynamics and body shape. We use a recurrent neural network to regress garment wrinkles, and we achieve highly plausible nonlinear effects, in contrast to the blending artifacts suffered by previous methods. At runtime, dynamic virtual try-on animations are produced in just a few milliseconds for garments with thousands of triangles. We show qualitative and quantitative analysis of results.
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