A Deep Learning Based Interactive Sketching System for Fashion Images Design
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Date
2020
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In this work, we propose an interactive system to design diverse high-quality garment images from fashion sketches and the texture information. The major challenge behind this system is to generate high-quality and detailed texture according to the user-provided texture information. Prior works mainly use the texture patch representation and try to map a small texture patch to a whole garment image, hence unable to generate high-quality details. In contrast, inspired by intrinsic image decomposition, we decompose this task into texture synthesis and shading enhancement. In particular, we propose a novel bi-colored edge texture representation to synthesize textured garment images and a shading enhancer to render shading based on the grayscale edges. The bi-colored edge representation provides simple but effective texture cues and color constraints, so that the details can be better reconstructed. Moreover, with the rendered shading, the synthesized garment image becomes more vivid.
Description
@inproceedings{10.2312:pg.20201224,
booktitle = {Pacific Graphics Short Papers, Posters, and Work-in-Progress Papers},
editor = {Lee, Sung-hee and Zollmann, Stefanie and Okabe, Makoto and Wuensche, Burkhard},
title = {{A Deep Learning Based Interactive Sketching System for Fashion Images Design}},
author = {Li, Yao and Yu, Xiang Gang and Han, Xiao Guang and Jiang, Nian Juan and Jia, Kui and Lu, Jiang Bo},
year = {2020},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-120-5},
DOI = {10.2312/pg.20201224}
}