Shadow detection and removal using GAN

Takahiro Nagae, Ryo Abiko, Takuro Yamaguchi, Masaaki Ikehara

研究成果: Conference contribution

抄録

To remove shadowed region in a single image, it is important to obtain high accuracy in both two processes, shadow detection and removal. In order to improve the results, recent methods perform these two processes simultaneously and use GAN for the training. However, since these methods do not try to maintain the luminance of non-shadowed regions, the output images tend to be faded. In this paper, to overcome fading problem, we proposed a new GAN structure based on shadow model. Since our GAN-based method focus on the variation of the illuminance, the illuminances of the shadowed regions, whose amount of change are large, are effectively estimated. In addition, non-shadowed regions remain slightly faded due to our new GAN structure and training method. Owing to our novel GAN structure and training method, our method outperforms state-of-the-art methods in PSNR and SSIM.

本文言語English
ホスト出版物のタイトル28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings
出版社European Signal Processing Conference, EUSIPCO
ページ630-634
ページ数5
ISBN(電子版)9789082797053
DOI
出版ステータスPublished - 2021 1 24
イベント28th European Signal Processing Conference, EUSIPCO 2020 - Amsterdam, Netherlands
継続期間: 2020 8 242020 8 28

出版物シリーズ

名前European Signal Processing Conference
2021-January
ISSN(印刷版)2219-5491

Conference

Conference28th European Signal Processing Conference, EUSIPCO 2020
CountryNetherlands
CityAmsterdam
Period20/8/2420/8/28

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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