Towards Book Cover Design via Layout Graphs

Wensheng Zhang, Yan Zheng, Taiga Miyazono, Seiichi Uchida, Brian Kenji Iwana

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

抄録

Book covers are intentionally designed and provide an introduction to a book. However, they typically require professional skills to design and produce the cover images. Thus, we propose a generative neural network that can produce book covers based on an easy-to-use layout graph. The layout graph contains objects such as text, natural scene objects, and solid color spaces. This layout graph is embedded using a graph convolutional neural network and then used with a mask proposal generator and a bounding-box generator and filled using an object proposal generator. Next, the objects are compiled into a single image and the entire network is trained using a combination of adversarial training, perceptual training, and reconstruction. Finally, a Style Retention Network (SRNet) is used to transfer the learned font style onto the desired text. Using the proposed method allows for easily controlled and unique book covers.

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642-657
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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