With the rise and development of deep learning, computer vision has been tremendously transformed and reshaped. As an important research area in computer vision, scene text detection and recognition has been inevitably influenced by this wave of revolution, consequentially entering the era of deep learning. In recent years, the community has witnessed substantial advancements in mindset, methodology and performance. This survey is aimed at summarizing and analyzing the major changes and significant progresses of scene text detection and recognition in the deep learning era. Through this article, we devote to: (1) introduce new insights and ideas; (2) highlight recent techniques and benchmarks; (3) look ahead into future trends. Specifically, we will emphasize the dramatic differences brought by deep learning and remaining grand challenges. We expect that this review paper would serve as a reference book for researchers in this field. Related resources are also collected in our Github repository ( https://github.com/Jyouhou/SceneTextPapers ).

中文翻译：

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场景文本检测与识别：深度学习时代

随着深度学习的兴起和发展，计算机视觉发生了巨大的转变和重塑。场景文本检测与识别作为计算机视觉的一个重要研究领域，不可避免地受到这波革命浪潮的影响，从而进入了深度学习时代。近年来，社区见证了思维方式、方法论和绩效方面的重大进步。本次调研旨在总结和分析深度学习时代场景文本检测与识别的主要变化和重大进展。通过这篇文章，我们致力于：（1）介绍新的见解和想法；(2) 突出最近的技术和基准；(3) 展望未来趋势。具体来说，我们将强调深度学习带来的巨大差异和剩余的巨大挑战。我们希望这篇综述论文可以作为该领域研究人员的参考书。我们的 Github 存储库 ( https://github.com/Jyouhou/SceneTextPapers ) 中也收集了相关资源。