Neural style difference transfer and its application to font generation

Gantugs Atarsaikhan, Brian Kenji Iwana, Seiichi Uchida

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 被引用数 (Scopus)

抄録

Designing fonts requires a great deal of time and effort. It requires professional skills, such as sketching, vectorizing, and image editing. Additionally, each letter has to be designed individually. In this paper, we introduce a method to create fonts automatically. In our proposed method, the difference of font styles between two different fonts is transferred to another font using neural style transfer. Neural style transfer is a method of stylizing the contents of an image with the styles of another image. We proposed a novel neural style difference and content difference loss for the neural style transfer. With these losses, new fonts can be generated by adding or removing font styles from a font. We provided experimental results with various combinations of input fonts and discussed limitations and future development for the proposed method.

本文言語英語
ホスト出版物のタイトルDocument Analysis Systems - 14th IAPR International Workshop, DAS 2020, Proceedings
編集者Xiang Bai, Dimosthenis Karatzas, Daniel Lopresti
出版社Springer
ページ544-558
ページ数15
ISBN(印刷版)9783030570576
DOI
出版ステータス出版済み - 2020
イベント14th IAPR International Workshop on Document Analysis Systems, DAS 2020 - Wuhan, 中国
継続期間: 7 26 20207 29 2020

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12116 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

会議

会議14th IAPR International Workshop on Document Analysis Systems, DAS 2020
国/地域中国
CityWuhan
Period7/26/207/29/20

All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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