Knowledge Commons of Institute of Automation,CAS
Handwritten Text Generation via Disentangled Representations | |
Liu, Xiyan1,2; Meng, Gaofeng1,2,3; Xiang, Shiming1,2; Pan, Chunhong1 | |
发表期刊 | IEEE SIGNAL PROCESSING LETTERS |
ISSN | 1070-9908 |
2021 | |
卷号 | 28期号:2021页码:1838-1842 |
摘要 | Automatically generating handwritten text images is a challenging task due to the diverse handwriting styles and the irregular writing in natural scenes. In this paper, we propose an effective generative model called HTG-GAN to synthesize handwritten text images from latent prior. Unlike single-character synthesis, our method is capable of generating images of sequence characters with arbitrary length, which pays more attention to the structural relationship between characters. We model the structural relationship as the style representation to avoid explicitly modeling the stroke layout. Specifically, the text image is disentangled into style representation and content representation, where the style representation is mapped into Gaussian distribution and the content representation is embedded using character index. In this way, our model can generate new handwritten text images with specified contents and various styles to perform data augmentation, thereby boosting handwritten text recognition (HTR). Experimental results show that our method achieves state-of-the-art performance in handwritten text generation. |
关键词 | Disentangled representation Handwritten text generation |
DOI | 10.1109/LSP.2021.3109541 |
关键词[WOS] | RECOGNITION ; SEQUENCE |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61976208] ; National Natural Science Foundation of China[62071466] |
项目资助者 | National Natural Science Foundation of China |
WOS研究方向 | Engineering |
WOS类目 | Engineering, Electrical & Electronic |
WOS记录号 | WOS:000697816900004 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 文字识别与文档分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/46047 |
专题 | 多模态人工智能系统全国重点实验室_先进时空数据分析与学习 中国科学院自动化研究所 |
通讯作者 | Meng, Gaofeng |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Ctr Artificial Intelligence & Robot, HK Inst Sci & Innovat, Hong Kong 999077, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Liu, Xiyan,Meng, Gaofeng,Xiang, Shiming,et al. Handwritten Text Generation via Disentangled Representations[J]. IEEE SIGNAL PROCESSING LETTERS,2021,28(2021):1838-1842. |
APA | Liu, Xiyan,Meng, Gaofeng,Xiang, Shiming,&Pan, Chunhong.(2021).Handwritten Text Generation via Disentangled Representations.IEEE SIGNAL PROCESSING LETTERS,28(2021),1838-1842. |
MLA | Liu, Xiyan,et al."Handwritten Text Generation via Disentangled Representations".IEEE SIGNAL PROCESSING LETTERS 28.2021(2021):1838-1842. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Handwritten_Text_Gen(1272KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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