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.

中文翻译：

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野外文本识别

文字的历史可以追溯到几千年前。文本承载的丰富而精准的语义信息在广泛的基于视觉的应用场景中具有重要意义。因此，自然场景中的文本识别一直是计算机视觉和模式识别领域的一个活跃研究课题。近年来，随着深度学习的兴起和发展，许多方法在创新性、实用性和效率方面都取得了可喜的成果。本文旨在 (1) 总结与场景文本识别相关的基本问题和最新技术，(2) 介绍新的见解和想法，(3) 提供对公开可用资源的全面回顾，以及 (4 ) 指出未来工作的方向。总之，这篇文献综述试图呈现场景文本识别领域的全貌。它为进入该领域的人们提供了全面的参考，并有助于启发未来的研究。相关资源可在我们的 GitHub 存储库中获得：https://github.com/HCIILAB/Scene-Text-Recognition。