Text Recognition in the Wild

Author:

Chen Xiaoxue1,Jin Lianwen2,Zhu Yuanzhi1,Luo Canjie1,Wang Tianwei1

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

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