Neural Font Style Transfer

Gantugs Atarsaikhan, Brian Kenji Iwana, Atsushi Narusawa, Keiji Yanai, Seiichi Uchida

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

10 被引用数 (Scopus)

抄録

In this paper, we chose an approach to generate fonts by using neural style transfer. Neural style transfer uses Convolution Neural Networks(CNN) to transfer the style of one image to another. By modifying neural style transfer, we can achieve neural font style transfer. We also demonstrate the effects of using different weighted factors, character placements, and orientations. In addition, we show the results of using non-Latin alphabets, non-text patterns, and non-text images as style images. Finally, we provide insight into the characteristics of style transfer with fonts.

本文言語英語
ホスト出版物のタイトルProceedings - 1st Workshop of Machine Learning under International Conference on Document Analysis and Recognition, ICDAR-WML 2017
出版社IEEE Computer Society
ページ51-56
ページ数6
ISBN(電子版)9781538635865
DOI
出版ステータス出版済み - 1 25 2018
イベント1st Workshop of Machine Learning under International Conference on Document Analysis and Recognition, ICDAR-WML 2017 - Kyoto, 日本
継続期間: 11 11 2017 → …

出版物シリーズ

名前Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
5
ISSN(印刷版)1520-5363

その他

その他1st Workshop of Machine Learning under International Conference on Document Analysis and Recognition, ICDAR-WML 2017
Country日本
CityKyoto
Period11/11/17 → …

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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引用スタイル