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ICDAR 2019 Robust Reading Challenge on Reading Chinese Text on Signboard

机译:Icdar 2019年在读取在牌的中国文本的强大读书挑战

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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:中国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,中文有超过6000个常用的字符,汉字可以以许多字体排列在各种布局中。街景中的招牌是中国场景文本图像的好选择,因为它们有不同的背景,字体和布局。我们组织了一个叫做ICDAR2019-RECTS的竞争,主要集中在招牌上阅读中文文本。本报告提出了竞争的最终结果。大规模数据集25,000个注释牌图像,其中所有文本行和字符都被释放出来,并释放了位置和转录。设置了四个任务,即字符识别,文本线识别,文本线路检测和端到端识别。此外,考虑到中国文本歧义问题,我们提出了一种多地面真理(多GT)评估方法,使评估更公平。比赛于2019年3月1日开始,并于2019年4月30日结束.262收到46支球队的提交。大多数参与者来自中国的大学,研究机构和科技公司。还有来自美国,澳大利亚,新加坡和韩国的一些参与者。 21团队提交任务1,23团队提交任务2的业绩,24个团队为任务3提交结果,13支队伍向任务提交结果。竞争的官方网站是http://rrc.cvc.uab。 ES /?CH = 12。

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