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ICDAR 2019 Robust Reading Challenge on Reading Chinese Text on Signboard

机译:ICDAR 2019在招牌上阅读中文文本的强大阅读挑战

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Chinese scene text reading is one of the most challenging problems in computer vision and has attracted great interest. Different from English text, Chinese has more than 6000 commonly used characters and Chinese characters can be arranged in various layouts with numerous fonts. The Chinese signboards in street view are a good choice for Chinese scene text images since they have different backgrounds, fonts and layouts. We organized a competition called ICDAR2019-ReCTS, which mainly focuses on reading Chinese text on signboard. This report presents the final results of the competition. A large-scale dataset of 25,000 annotated signboard images, in which all the text lines and characters are annotated with locations and transcriptions, were released. Four tasks, namely character recognition, text line recognition, text line detection and end-to-end recognition were set up. Besides, considering the Chinese text ambiguity issue, we proposed a multi ground truth (multi-GT) evaluation method to make evaluation fairer. The competition started on March 1, 2019 and ended on April 30, 2019. 262 submissions from 46 teams are received. Most of the participants come from universities, research institutes, and tech companies in China. There are also some participants from the United States, Australia, Singapore, and Korea. 21 teams submit results for Task 1, 23 teams submit results for Task 2, 24 teams submit results for Task 3, and 13 teams submit results for Task 4. The official website for the competition is http://rrc.cvc.uab.es/?ch=12.
机译:中文场景文本阅读是计算机视觉中最具挑战性的问题之一,并引起了极大的兴趣。与英文文本不同,中文具有6000多个常用字符,中文字符可以以多种字体排列的各种布局。街景中的中文招牌是中文场景文字图像的不错选择,因为它们具有不同的背景,字体和布局。我们举办了一项名为ICDAR2019-ReCTS的比赛,该比赛主要侧重于在招牌上阅读中文文本。本报告介绍了比赛的最终结果。发布了包含25,000个带注释的招牌图像的大规模数据集,其中所有文本行和字符都带有位置和文字注释。设置了四个任务,即字符识别,文本行识别,文本行检测和端到端识别。此外,考虑到中文文本的歧义性问题,我们提出了一种多地面真相(multi-GT)评估方法,以使评估更加公平。比赛于2019年3月1日开始,至2019年4月30日结束。共收到来自46个团队的262份参赛作品。大多数参与者来自中国的大学,研究机构和科技公司。也有来自美国,澳大利亚,新加坡和韩国的一些参与者。 21支团队提交任务1的结果,23支团队提交任务2的结果,24支团队提交任务3的结果,13支团队提交任务4的结果。比赛的官方网站是http://rrc.cvc.uab。 es /?ch = 12。

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