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

TL;DR

This paper presents the results and dataset of the ICDAR2019 challenge on recognizing arbitrary-shaped text in images, covering detection, recognition, and spotting tasks with detailed evaluation metrics and participant methods.

Contribution

It introduces the ArT dataset, challenge tasks, and evaluation framework for arbitrary-shaped scene text recognition, providing a benchmark for future research.

Findings

Top detection score: 82.65%

Recognition accuracy up to 74.3% and 85.32% in respective tasks

Results and dataset are publicly available

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 methods. The dataset, the evaluation kit as well as the results are publicly available at https://rrc.cvc.uab.es/?ch=14