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ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT)

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arxiv 1909.07145 v1 pith:DRGSW6KO submitted 2019-09-16 cs.CV

Chee-Kheng Chng , Yuliang Liu , Yipeng Sun , Chun Chet Ng , Canjie Luo , Zihan Ni , ChuanMing Fang , Shuaitao Zhang
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Junyu Han Errui Ding Jingtuo Liu Dimosthenis Karatzas Chee Seng Chan Lianwen Jin
This is my paper · ORCID
classification cs.CV
keywords textchallengescenearbitrary-shapeddatasetevaluationicdar2019reading
verification ladder T0 review T1 audit T2 compute T3 formal
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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

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