Text Perceptron: Towards End-to-End Arbitrary-Shaped Text Spotting

Understand

Many approaches have recently been proposed to detect irregular scene text and achieved promising results.

• However, their localization results may not well satisfy the following text recognition part mainly because of two reasons: 1) recognizing arbitrary shaped text is still a challenging task, and 2) prevalent non-trainable pipeline strategies between text detection and text recognition will lead to suboptimal performances.
• To handle this incompatibility problem, in this paper we propose an end-to-end trainable text spotting approach named Text Perceptron.
• Concretely, Text Perceptron first employs an efficient segmentation-based text detector that learns the latent text reading order and boundary information.