UVTON: UV Mapping to Consider the 3D Structure of a Human in Image-Based Virtual Try-On Network

Shizuma Kubo, Yusuke Iwasawa, Masahiro Suzuki, Yutaka Matsuo; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 0-0

Abstract


Image-based virtual try-on is an area of research that is attracting attention as the demand for online apparel shopping continues to increase. The methods proposed thus far have focused on how to generate a dress-up image while preserving the clothing details. However, the posture of the model in the image is limited to an upright position, and other positions frequently do not work well. In this study, based on a kind of generative adversarial network (GAN) that utilizes UV mapping to consider the 3D structure of the human body, we propose a novel virtual try-on method called a UV Try-On Network (UVTON). We use a DensePose to estimate a point corresponding to the 3D surface of a human model for each pixel point of a 2D image and incorporate the estimated information into our model. It is thus possible to change the clothes of users holding various postures. Our proposed method uses UV mapping and two other modules. One module generates parts to be used in the mapping, and the other refines the image and produces a more realistic image. Based on both qualitative and quantitative comparison with existing methods, we experimentally demonstrated that our method achieved better results with various postures.

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[bibtex]
@InProceedings{Kubo_2019_ICCV,
author = {Kubo, Shizuma and Iwasawa, Yusuke and Suzuki, Masahiro and Matsuo, Yutaka},
title = {UVTON: UV Mapping to Consider the 3D Structure of a Human in Image-Based Virtual Try-On Network},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2019}
}