ICPR2018 Contest on Robust Reading for Multi-Type Web Images

Electronic commerce has infiltrated every aspect of our daily lives, which offers great convenience for shopping, advertising, etc. Text in the web images is responsible to convey essential information for consumers. Algorithms that read text in these web images can facilitate applications of various types, such as goods surveillance, products classification, and intelligent retrieval or recommendation. Despite of various existing text reading tasks, this contest introduces a novel large-scale dataset named MTWI that contains 20,000 images, which is the first dataset that is mainly constructed by Chinese and English web text. Three tasks (web text recognition, web text detection, and end-to-end web text detection and recognition) were set up for encouraging more research on the web text reading problem. The contest was held from February 2, 2018 to May 26, 2018 with 289 valid submissions from 4,282 registered teams. Throughout this report, we describe the details of this new dataset, the purposes and definitions of the tasks, the evaluation protocols, and the summaries of the results.

I. Introduction

Electronic commerce offers great convenience for shopping or advertising, which is now becoming an indispensable part of our life. Driven by the increasing demand of consumers, more and more products are available for online-shopping, thousands of web images have been generated simultaneously. Text in these web images is one of the most essential forms to convey valuable information. The web text ability can facilitate applications of various kinds, such as goods surveillance, products classification, content filtering and intelligent retrieval or recommendation.