Affiliation:
1. South China University of Technology, Guangzhou, China
2. South China University of Technology, China and SCUT-Zhuhai Institute of Modern Industrial Innovation, Zhuhai, China
Abstract
The history of text can be traced back over thousands of years. Rich and precise semantic information carried by text is important in a wide range of vision-based application scenarios. Therefore, text recognition in natural scenes has been an active research topic in computer vision and pattern recognition. In recent years, with the rise and development of deep learning, numerous methods have shown promising results in terms of innovation, practicality, and efficiency. This article aims to (1) summarize the fundamental problems and the state-of-the-art associated with scene text recognition, (2) introduce new insights and ideas, (3) provide a comprehensive review of publicly available resources, and (4) point out directions for future work. In summary, this literature review attempts to present an entire picture of the field of scene text recognition. It provides a comprehensive reference for people entering this field and could be helpful in inspiring future research. Related resources are available at our GitHub repository: https://github.com/HCIILAB/Scene-Text-Recognition.
Funder
Guangdong Intellectual Property Office Project
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Cited by
103 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献