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 field in computer vision and pattern recognition. In recent years, with the rise and development of deep learning, numerous methods have shown promising in terms of innovation, practicality, and efficiency. This paper 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; (4) point out directions for future work. In summary, this literature review attempts to present the entire picture of the field of scene text recognition. It provides a comprehensive reference for people entering this field, and could be helpful to inspire future research. Related resources are available at our Github repository: https://github.com/HCIILAB/Scene-Text-Recognition.
翻译:文本的历史可以追溯到数千年的时间里。通过文本传播的丰富而精确的语义信息在广泛的基于愿景的应用情景中非常重要。因此,自然场景的文本识别一直是计算机视觉和模式识别的一个积极研究领域。近年来,随着深层次学习的兴起和发展,许多方法在创新、实用性和效率方面都显示出了希望。本文件旨在:(1) 总结与现场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) 全面审查公开可得的资源;(4) 指出未来工作的方向。概括地说,本文献审查试图介绍现场文本识别领域的全部情况。它为进入这一领域的人提供了一个全面的参考,有助于激发未来的研究。相关的资源可以在我们的Github 存放处获得: https://github.com/HCIILAB/Scene-Text-Recognition。