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Scene text detection and recognition with advances in deep learning: a survey

机译:场景文本检测和识别与深度学习的进步:一项调查

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摘要

Scene text detection and recognition has become a very active research topic in recent several years. It can find many applications in reality ranging from navigation for vision-impaired people to semantic natural scene understanding. In this survey, we are intended to give a thorough and in-depth reviews on the recent advances on this topic, mainly focusing on the methods that appeared in the past 5years for text detection and recognition in images and videos, including the recent state-of-the-art techniques on the following three related topics: (1) scene text detection, (2) scene text recognition and (3) end-to-end text recognition system. Compared with the previous survey, this survey pays more attention to the application of deep learning techniques on scene text detection and recognition. We also give a brief introduction of other related works such as script identification, texton-text classification and text-to-image retrieval. This survey also reviews and summarizes some benchmark datasets that are widely used in the literature. Based on these datasets, performances of state-of-the-art approaches are shown and discussed. Finally, we conclude this survey by pointing out several potential directions on scene text detection and recognition that need to be well explored in the future.
机译:近年来,场景文本的检测和识别已经成为非常活跃的研究课题。它可以在现实中找到许多应用,从为视障人士导航到语义自然场景理解。在本次调查中,我们打算就该主题的最新进展进行彻底而深入的评论,主要着眼于过去5年中出现的用于图像和视频中文本检测和识别的方法,包括最近的状态-以下三个相关主题的最新技术:(1)场景文本检测,(2)场景文本识别和(3)端到端文本识别系统。与之前的调查相比,该调查更加关注深度学习技术在场景文本检测和识别中的应用。我们还简要介绍了其他相关工作,例如脚本识别,文本/非文本分类和文本到图像检索。该调查还回顾并总结了一些文献中广泛使用的基准数据集。基于这些数据集,显示和讨论了最新方法的性能。最后,我们通过指出场景文本检测和识别的几个潜在方向来结束本调查,这些方向将来需要很好地探索。

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