ICDAR2017 Competition on Reading Chinese Text in the Wild (RCTW-17)
It addresses the lack of datasets and competitions for Chinese text reading, which is important for applications in Chinese-speaking regions, but is incremental as it extends existing text reading frameworks to a new language.
The paper introduces RCTW-17, a competition focused on reading Chinese text in natural images, featuring a dataset of 12,263 annotated images and tasks for text localization and end-to-end recognition, with 23 submissions from 19 teams.
Chinese is the most widely used language in the world. Algorithms that read Chinese text in natural images facilitate applications of various kinds. Despite the large potential value, datasets and competitions in the past primarily focus on English, which bares very different characteristics than Chinese. This report introduces RCTW, a new competition that focuses on Chinese text reading. The competition features a large-scale dataset with 12,263 annotated images. Two tasks, namely text localization and end-to-end recognition, are set up. The competition took place from January 20 to May 31, 2017. 23 valid submissions were received from 19 teams. This report includes dataset description, task definitions, evaluation protocols, and results summaries and analysis. Through this competition, we call for more future research on the Chinese text reading problem. The official website for the competition is http://rctw.vlrlab.net