@InProceedings{Chee-KhengChng2019,
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",
title="ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text -- RRC-ArT",
booktitle="15th International Conference on Document Analysis and Recognition",
year="2019",
pages="1571--1576",
abstract="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{\textquoteright} methods. The dataset, the evaluation kit as well as the results are publicly available at the challenge website.",
optnote="DAG; 600.121; 600.129",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3340), last updated on Tue, 25 Jan 2022 11:03:18 +0100",
doi="10.1109/ICDAR.2019.00252",
opturl="https://ieeexplore.ieee.org/document/8978157",
file=":http://refbase.cvc.uab.es/files/CLS2019.pdf:PDF"
}