Detecting and reading text in natural images (also referred to as Scene Text or text in the wild) has been a central problem in scene understanding with applications ranging from helping visually impaired people navigate city scenes to product search and retrieval, and instant translation. Scene Text is typically broken down into two successive tasks: (1) text detection attempts to localize characters, words or lines, and (2) text recognition aims to transcribe their content.
Recently, segmentation-based methods are quite popular in scene text detection, as the segmentation results can more accurately describe scene text of various shapes such as curve text.
Ranked #2 on Scene Text Detection on MSRA-TD500
Detecting scene text of arbitrary shapes has been a challenging task over the past years.
We show that the model is able to recognize several types of irregular text, including perspective text and curved text.
Ranked #6 on Scene Text Recognition on ICDAR 2003
In this paper, we investigate the problem of scene text recognition, which is among the most important and challenging tasks in image-based sequence recognition.
Ranked #8 on Scene Text Recognition on ICDAR 2003
The goal of COCO-Text is to advance state-of-the-art in text detection and recognition in natural images.