Deep Detail Enhancement for Any Garment

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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
Creating fine garment details requires significant efforts and huge computational resources. In contrast, a coarse shape may be easy to acquire in many scenarios (e.g., via low-resolution physically-based simulation, linear blend skinning driven by skeletal motion, portable scanners). In this paper, we show how to enhance, in a data-driven manner, rich yet plausible details starting from a coarse garment geometry. Once the parameterization of the garment is given, we formulate the task as a style transfer problem over the space of associated normal maps. In order to facilitate generalization across garment types and character motions, we introduce a patch-based formulation, that produces high-resolution details by matching a Gram matrix based style loss, to hallucinate geometric details (i.e., wrinkle density and shape). We extensively evaluate our method on a variety of production scenarios and show that our method is simple, light-weight, efficient, and generalizes across underlying garment types, sewing patterns, and body motion. Project page: http://geometry.cs.ucl.ac.uk/projects/2021/DeepDetailEnhance/
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@article{
10.1111:cgf.142642
, journal = {Computer Graphics Forum}, title = {{
Deep Detail Enhancement for Any Garment
}}, author = {
Zhang, Meng
and
Wang, Tuanfeng
and
Ceylan, Duygu
and
Mitra, Niloy J.
}, year = {
2021
}, publisher = {
The Eurographics Association and John Wiley & Sons Ltd.
}, ISSN = {
1467-8659
}, DOI = {
10.1111/cgf.142642
} }
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