ICDAR2017 Robust Reading Challenge on COCO-Text

被引:32
作者
Gomez, Raul [1 ]
Shi, Baoguang [2 ]
Gomez, Lluis [3 ]
Neumann, Lukas [4 ]
Veit, Andreas [5 ,6 ]
Matas, Jiri [4 ]
Belongie, Serge [5 ,6 ]
Karatzas, Dimosthenis [3 ]
机构
[1] Univ Autonoma Barcelona & Eurecat, Comp Vis Ctr, Barcelona, Spain
[2] Huazhong Univ Sci & Technol, Sch EIC, Wuhan, Hubei, Peoples R China
[3] Univ Autonoma Barcelona, Comp Vis Ctr, Barcelona, Spain
[4] Czech Tech Univ, Ctr Machine Percept, Prague, Czech Republic
[5] Cornell Univ, Ithaca, NY USA
[6] Cornell Tech, New York, NY USA
来源
2017 14TH IAPR INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR), VOL 1 | 2017年
关键词
D O I
10.1109/ICDAR.2017.234
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This report presents the final results of the ICDAR 2017 Robust Reading Challenge on COCO-Text. A challenge on scene text detection and recognition based on the largest real scene text dataset currently available: the COCO-Text dataset [1]. The competition is structured around three tasks: Text Localization, Cropped Word Recognition and End-To-End Recognition. The competition received a total of 27 submissions over the different opened tasks. This report describes the datasets and the ground truth, details the performance evaluation protocols used and presents the final results along with a brief summary of the participating methods.
引用
收藏
页码:1435 / 1443
页数:9
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