A study of fabric estimation using CNN from clothes images

Yuki Kanai; Yoshitsugu Manabe; Noriko Yata

doi:10.1117/12.2590973

13 March 2021 A study of fabric estimation using CNN from clothes images

Yuki Kanai, Yoshitsugu Manabe, Noriko Yata

Proceedings Volume 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021; 117660O (2021) https://doi.org/10.1117/12.2590973
Event: International Workshop on Advanced Imaging Technology 2021 (IWAIT 2021), 2021, Online Only

Abstract

In recent years, research on virtual fitting has been conducted in the fashion field. Many of them have been put to practical use in prepared clothes, and companies are using the information on the shape, size, and fabric of their clothes to provide users with virtual fitting. In the case without known data, there are many methods of estimating the shape and size of the clothes in images. Using these methods, users can try on virtually the clothes they want to wear while fitting the users’ body shape and pose. On the other hand, a method for estimating the fabric of clothes remains to be developed. Because the materials of clothes are related to the softness of clothes in virtual fitting, it is difficult to reproduce the realistic movements and wrinkles of clothes using the conventional virtual fitting system. This study proposes a method for estimating the material of fabric from clothes images, aiming at realistic virtual fitting. A dataset focusing on each fabric’s texture and luster is constructed and estimated using a Convolutional Neural Network (CNN).

Citation Download Citation

Yuki Kanai, Yoshitsugu Manabe, and Noriko Yata "A study of fabric estimation using CNN from clothes images", Proc. SPIE 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021, 117660O (13 March 2021); https://doi.org/10.1117/12.2590973

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