TY - CHAP
T1 - ICDAR 2019 robust reading challenge on reading chinese text on signboard
AU - Zhang, Rui
AU - Yang, Mingkun
AU - Bai, Xiang
AU - Shi, Baoguang
AU - Karatzas, Dimosthenis
AU - Lu, Shijian
AU - Jawahar, C. V.
AU - Zhou, Yongsheng
AU - Jiang, Qianyi
AU - Song, Qi
AU - Li, Nan
AU - Zhou, Kai
AU - Wang, Lei
AU - Wang, Dong
AU - Liao, Minghui
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - 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.
AB - 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.
KW - Chinese text
KW - ReCTS
KW - Robust reading
KW - Scene text reading
KW - Signboard
UR - https://www.scopus.com/pages/publications/85079890842
U2 - 10.1109/ICDAR.2019.00253
DO - 10.1109/ICDAR.2019.00253
M3 - Chapter
AN - SCOPUS:85079890842
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 1577
EP - 1581
BT - Proceedings - 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019
ER -