ICDAR 2015 Text Reading in the Wild Competition
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Abstract (arXiv)
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.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Jun 2015.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 2; 2024: 0; 2025: 1; 2026: 2.
8 papers.
- 2021From Two to One: A New Scene Text Recognizer with Visual Language Modeling Networkcited by 97
- 2022ABINet++: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Spottingcited by 40
- 2021A Bilingual, OpenWorld Video Text Dataset and End-to-end Video Text Spotter with Transformercited by 26
- 2023ICDAR 2023 Video Text Reading Competition for Dense and Small Textcited by 9
- 2023DSText V2: A Comprehensive Video Text Spotting Dataset for Dense and Small Textcited by 7
- 2025PLATTER: A Page-Level Handwritten Text Recognition System for Indic Scriptscited by 2
- 2026Policy-based Foveated Imaging and Perceptioncited by 1
- 2026Back-Tracking from Clarity: Self-Learning to See Text from Afarcited by 0
- 2026Back-Tracking from Clarity: Self-Learning to See Text from Afar26 Sep 2026
- 2026Policy-based Foveated Imaging and Perception1 Jun 2026
- 2025PLATTER: A Page-Level Handwritten Text Recognition System for Indic Scripts10 Feb 2025
- 2023DSText V2: A Comprehensive Video Text Spotting Dataset for Dense and Small Text29 Nov 2023
- 2023ICDAR 2023 Video Text Reading Competition for Dense and Small Text10 Apr 2023
- 2022ABINet++: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Spotting19 Nov 2022
- 2021A Bilingual, OpenWorld Video Text Dataset and End-to-end Video Text Spotter with Transformer9 Dec 2021
- 2021From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network22 Aug 2021