Cross-Lingual Text Image Recognition via Multi-Hierarchy Cross-Modal Mimic

doi:10.1109/TMM.2022.3183386

	Cross-Lingual Text Image Recognition via Multi-Hierarchy Cross-Modal Mimic
	Chen, Zhuo1,2 ; Yin, Fei1,2 ; Yang, Qing1,2 ; Liu, Cheng-Lin1,2
发表期刊	IEEE TRANSACTIONS ON MULTIMEDIA
ISSN	1520-9210
	2023
卷号	25 页码:4830-4841
通讯作者	Liu, Cheng-Lin(liucl@nlpr.ia.ac.cn)
摘要	Optical character recognition and machine translation are usually studied and applied separately. In this paper, we consider a new problem named cross-lingual text image recognition (CLTIR) that integrates these two tasks together. The core of this problem is to recognize source language texts shown in images and transcribe them to the target language in an end-to-end manner. Traditional cascaded systems perform text image recognition and text translation sequentially. This can lead to error accumulation and parameter redundancy problems. To overcome these problems, we propose a multihierarchy cross-modal mimic (MHCMM) framework for end-to-end CLTIR, which can be trained with a massive bilingual text corpus and a small number of bilingual annotated text images. In this framework, a plug-in machine translation model is used as a teacher to guide the CLTIR model for learning representations compatible with image and text modes. Via adversarial learning and attention mechanisms, the proposed mimic method can integrate both global and local information in the semantic space. Experiments on a newly collected dataset demonstrate the superiority of the proposed framework. Our method outperforms other pipelines while containing fewer parameters. Additionally, the MHCMM framework can utilize a large-scale bilingual corpus to further improve the performance efficiently. The visualization of attention scores indicates that the proposed model can read text images in a fashion similar to the machine translation model reading text tokens.
关键词	Cross-lingual text image recognition cross-modal mimic multihierarchy mimic
DOI	10.1109/TMM.2022.3183386
关键词[WOS]	SCENE TEXT
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program[2020AAA0108003] ; National Natural Science Foundation of China[61733007] ; National Natural Science Foundation of China[61721004]
项目资助者	National Key Research and Development Program ; National Natural Science Foundation of China
WOS研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS记录号	WOS:001097340300016
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/55205
专题	多模态人工智能系统全国重点实验室
通讯作者	Liu, Cheng-Lin
作者单位	1.Chinese Acad Sci, Natl Lab Pattern Recognit NLPR, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, 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	Chen, Zhuo,Yin, Fei,Yang, Qing,et al. Cross-Lingual Text Image Recognition via Multi-Hierarchy Cross-Modal Mimic[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2023,25:4830-4841.
APA	Chen, Zhuo,Yin, Fei,Yang, Qing,&Liu, Cheng-Lin.(2023).Cross-Lingual Text Image Recognition via Multi-Hierarchy Cross-Modal Mimic.IEEE TRANSACTIONS ON MULTIMEDIA,25,4830-4841.
MLA	Chen, Zhuo,et al."Cross-Lingual Text Image Recognition via Multi-Hierarchy Cross-Modal Mimic".IEEE TRANSACTIONS ON MULTIMEDIA 25(2023):4830-4841.