Font Style that Fits an Image – Font Generation Based on Image Context

Taiga Miyazono, Brian Kenji Iwana, Daichi Haraguchi, Seiichi Uchida

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

抄録

When fonts are used on documents, they are intentionally selected by designers. For example, when designing a book cover, the typography of the text is an important factor in the overall feel of the book. In addition, it needs to be an appropriate font for the rest of the book cover. Thus, we propose a method of generating a book title image based on its context within a book cover. We propose an end-to-end neural network that inputs the book cover, a target location mask, and a desired book title and outputs stylized text suitable for the cover. The proposed network uses a combination of a multi-input encoder-decoder, a text skeleton prediction network, a perception network, and an adversarial discriminator. We demonstrate that the proposed method can effectively produce desirable and appropriate book cover text through quantitative and qualitative results. The code can be found at https://github.com/Taylister/FontFits.

本文言語英語
ホスト出版物のタイトルDocument Analysis and Recognition - ICDAR 2021 - 16th International Conference, Proceedings
編集者Josep Lladós, Daniel Lopresti, Seiichi Uchida
出版社Springer Science and Business Media Deutschland GmbH
ページ569-584
ページ数16
ISBN(印刷版)9783030863333
DOI
出版ステータス出版済み - 2021
イベント16th International Conference on Document Analysis and Recognition, ICDAR 2021 - Lausanne, スイス
継続期間: 9 5 20219 10 2021

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)
12823 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

会議

会議16th International Conference on Document Analysis and Recognition, ICDAR 2021
国/地域スイス
CityLausanne
Period9/5/219/10/21

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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