Attention-Aware Anime Line Drawing Colorization

Yu Cao, Hao Tian, P. Y. Mok (Corresponding Author)

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Automatic colorization of anime line drawing has attracted much attention in recent years since it can substantially benefit the animation industry. User-hint based methods are the mainstream approach for line drawing colorization, while reference-based methods offer a more intuitive approach. Nevertheless, although reference-based methods can improve feature aggregation of the reference image and the line drawing, the colorization results are not compelling in terms of color consistency or semantic correspondence. In this paper, we introduce an attention-based model for anime line drawing colorization, in which a channel-wise and spatial-wise Convolutional Attention module is used to improve the ability of the encoder for feature extraction and key area perception, and a Stop-Gradient Attention module with cross-attention and self-attention is used to tackle the cross-domain long-range dependency problem. Extensive experiments show that our method outperforms other SOTA methods, with more accurate line structure and semantic color information.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE International Conference on Multimedia and Expo, ICME 2023
PublisherIEEE Computer Society
Pages1637-1642
Number of pages6
ISBN (Electronic)9781665468916
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Multimedia and Expo, ICME 2023 - Brisbane, Australia
Duration: 10 Jul 202314 Jul 2023

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
Volume2023-July
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Conference

Conference2023 IEEE International Conference on Multimedia and Expo, ICME 2023
Country/TerritoryAustralia
CityBrisbane
Period10/07/2314/07/23

Keywords

  • Attention Mechanism
  • Conditional Generation
  • Line Drawing Colorization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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