This paper reports the ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT) that consists of three major challenges: i) scene text detection, ii) scene text recognition, and iii) scene text spotting. A total of 78 submissions from 46 unique teams/individuals were received for this competition. The top performing score of each challenge is as follows: i) T1 - 82.65%, ii) T2.1 - 74.3%, iii) T2.2 - 85.32%, iv) T3.1 - 53.86%, and v) T3.2 - 54.91%. Apart from the results, this paper also details the ArT dataset, tasks description, evaluation metrics and participants methods. The dataset, the evaluation kit as well as the results are publicly available at https://rrc.cvc.uab.es/?ch=14
@article{arxiv.1909.07145,
title = {ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT)},
author = {Chee-Kheng Chng and Yuliang Liu and Yipeng Sun and Chun Chet Ng and Canjie Luo and Zihan Ni and ChuanMing Fang and Shuaitao Zhang and Junyu Han and Errui Ding and Jingtuo Liu and Dimosthenis Karatzas and Chee Seng Chan and Lianwen Jin},
journal= {arXiv preprint arXiv:1909.07145},
year = {2019}
}
Comments
Technical report of ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT) Competition