ICDAR 2015 Text Reading in the Wild Competition

TL;DR

This paper reports on the ICDAR 2015 Text Reading in the Wild competition, establishing benchmarks for detecting and recognizing Chinese and English text in natural scenes, and discusses dataset, evaluation, and future research directions.

Contribution

It introduces a benchmark for multilingual text detection and recognition in natural scenes, including dataset, evaluation protocols, and analysis of participant methods.

Findings

Performance benchmarks for Chinese and English text recognition.

Analysis of participating methods and their effectiveness.

Discussion of future research directions in scene text recognition.

Abstract

Recently, text detection and recognition in natural scenes are becoming increasing popular in the computer vision community as well as the document analysis community. However, majority of the existing ideas, algorithms and systems are specifically designed for English. This technical report presents the final results of the ICDAR 2015 Text Reading in the Wild (TRW 2015) competition, which aims at establishing a benchmark for assessing detection and recognition algorithms devised for both Chinese and English scripts and providing a playground for researchers from the community. In this article, we describe in detail the dataset, tasks, evaluation protocols and participants of this competition, and report the performance of the participating methods. Moreover, promising directions for future research are discussed.