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research-article

Text Recognition in the Wild: A Survey

Authors:

Tianwei WangAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 54, Issue 2

Article No.: 42, Pages 1 - 35

https://doi.org/10.1145/3440756

Published: 05 March 2021 Publication History

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.

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Index Terms

Text Recognition in the Wild: A Survey
1. Applied computing
  1. Document management and text processing
    1. Document capture
      1. Optical character recognition
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object recognition

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 54, Issue 2

March 2022

800 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3450359

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Accepted: 01 December 2020

Received: 01 July 2019

Published in CSUR Volume 54, Issue 2

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