Line art colorization with concatenated spatial attention

Mingcheng Yuan, Edgar Simo-Serra

研究成果: Conference contribution

抄録

Line art plays a fundamental role in illustration and design, and allows for iteratively polishing designs. However, as they lack color, they can have issues in conveying final designs. In this work, we propose an interactive colorization approach based on a conditional generative adversarial network that takes both the line art and color hints as inputs to produce a high-quality colorized image. Our approach is based on a U-net architecture with a multi-discriminator framework. We propose a Concatenation and Spatial Attention module that is able to generate more consistent and higher quality of line art colorization from user given hints. We evaluate on a large-scale illustration dataset and comparison with existing approaches corroborate the effectiveness of our approach.

本文言語English
ホスト出版物のタイトルProceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
出版社IEEE Computer Society
ページ3941-3945
ページ数5
ISBN(電子版)9781665448994
DOI
出版ステータスPublished - 2021 6
イベント2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021 - Virtual, Online, United States
継続期間: 2021 6 192021 6 25

出版物シリーズ

名前IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN(印刷版)2160-7508
ISSN(電子版)2160-7516

Conference

Conference2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
国/地域United States
CityVirtual, Online
Period21/6/1921/6/25

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識
  • 電子工学および電気工学

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