Deep TextSpotter: An End-to-End Trainable Scene Text Localization and Recognition Framework

被引:165
作者
Busta, Michal [1 ]
Neumann, Lukas [1 ]
Matas, Jiri [1 ]
机构
[1] Czech Tech Univ, Ctr Machine Percept, Dept Cybernet, Prague, Czech Republic
来源
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) | 2017年
关键词
D O I
10.1109/ICCV.2017.242
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A method for scene text localization and recognition is proposed. The novelties include: training of both text detection and recognition in a single end-to-end pass, the structure of the recognition CNN and the geometry of its input layer that preserves the aspect of the text and adapts its resolution to the data. The proposed method achieves state-of-the-art accuracy in the end-to-end text recognition on two standard datasets - ICDAR 2013 and ICDAR 2015, whilst being an order of magnitude faster than competing methods - the whole pipeline runs at 10 frames per second on an NVidia K80 GPU.
引用
收藏
页码:2223 / 2231
页数:9
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