%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2020/09.25.12.14
%2 sid.inpe.br/sibgrapi/2020/09.25.12.14.30
%@doi 10.1109/SIBGRAPI51738.2020.00037
%T Weakly Supervised Character Detection for License Plate Recognition
%D 2020
%A Zeni, Luis Felipe,
%A Jung, Claudio,
%@affiliation Universidade Federal do Rio Grande do Sul
%@affiliation Universidade Federal do Rio Grande do Sul
%E Musse, Soraia Raupp,
%E Cesar Junior, Roberto Marcondes,
%E Pelechano, Nuria,
%E Wang, Zhangyang (Atlas),
%B Conference on Graphics, Patterns and Images, 33 (SIBGRAPI)
%C Porto de Galinhas (virtual)
%8 7-10 Nov. 2020
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K weakly supervised character detection, licence plate recognition, character detection, neural networks.
%X Automatic Licence Plate Recognition (ALPR) is an essential task in the context of intelligent transportation systems. In a typical ALPR pipeline, the last stage receives as input a cropped license plate region and outputs the string with the plate characters. This paper presents a Weakly Supervised Character Detection (WSCD) approach that requires only string-level annotations (as in generic text recognition methods) but is able to detect characters individually (as in detection-based methods, which require character-level annotations). The proposed method is evaluated in five distinct datasets and present very competitive results against other state-of-the-art methods.
%@language en
%3 21.pdf