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

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

arXiv commentTechnical report of ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT) Competition

References in corpus (2)

• COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images
• Detecting Curve Text in the Wild: New Dataset and New Solution

Cited by in corpus (5)

• Text Recognition in the Wild: A Survey
• Structured Multimodal Attentions for TextVQA
• FedOCR: Communication-Efficient Federated Learning for Scene Text Recognition
• Exploring the Capacity of an Orderless Box Discretization Network for Multi-orientation Scene Text Detection
• A Feasible Framework for Arbitrary-Shaped Scene Text Recognition