Cross-lingual font style transfer with full-domain convolutional attention

首页 > 成果 > 详情

认领

导出

Link by DOI

反馈

作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Zhao, Hui-huang;Ji, Tian-le;Rosin, Paul L.;Lai, Yu-Kun;Meng, Wei-liang;...

通讯作者：

Zhao, HH

作者机构：

[Zhao, Hui-huang; Wang, Yao-nan] Hengyang Normal Univ, Sch Comp Sci & Technol, Hengyang 421002, Peoples R China.

[Ji, Tian-le; Zhao, Hui-huang] Hunan Univ, Natl Engn Lab Robot Visual Percept & Control Techn, Changsha, Peoples R China.

[Lai, Yu-Kun; Rosin, Paul L.] Cardiff Univ, Sch Comp Sci & Informat, Cardiff, Wales.

[Meng, Wei-liang] Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100098, Peoples R China.

[Meng, Wei-liang] Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China.

通讯机构：

[Zhao, HH ] H

Hengyang Normal Univ, Sch Comp Sci & Technol, Hengyang 421002, Peoples R China.

Hunan Univ, Natl Engn Lab Robot Visual Percept & Control Techn, Changsha, Peoples R China.

语种：

英文

关键词：

Cross-lingual;Full-domain convolutional attention;Multi-layer perceptual discriminator;Font style transfer

期刊：

Pattern Recognition

ISSN：

0031-3203

年：

2024

卷：

155

DOI：

10.1016/j.patcog.2024.110709

基金类别：

National Natural Science Foundation of China [61772179]; Hunan Provincial Natural Science Foundation of China [2024JJ5059, 2023JJ50095, 2022JJ50016]; The 14th Five-Year Plan"Key Disciplines and Application-oriented Special Disciplines of Hunan Province [[2022] 351]; Science and Technology Plan Project of Hunan Province, China [2016TP1020]

机构署名：

本校为第一且通讯机构

摘要：

In this paper, we propose a new cross -lingual font style transfer model, FCAGAN, which enables font style transfer between different languages by observing a small number of samples. Most previous work has been on style transfer of different fonts for single language content, but in our task we can learn the font style of one language and migrate it to another. We investigated the drawbacks of related studies and found that existing cross -lingual approaches cannot perfectly learn styles from other languages and maintain the integrity of their own content. Therefore, we designed a new full -d...

反馈

产权有误：本人成果被他人认领

数据有误：数据基本信息有误

归属有误：成果的院系归属、机构署名归属有误

其他原因：

验证码：

看不清楚，换一个

确定

取消

成果认领

标题：

用户	作者	通讯作者	--
	请选择	请选择	--

确定

取消

Cross-lingual font style transfer with full-domain convolutional attention

反馈

成果认领

提示

该栏目需要登录且有访问权限才可以访问