The history of text can be traced back over thousands of years. Rich and precise semantic
information carried by text is important in a wide range of vision-based application …

Linguistic knowledge is of great benefit to scene text recognition. However, how to effectively
model linguistic rules in end-to-end deep networks remains a research challenge. In this …

In this paper, we abandon the dominant complex language model and rethink the linguistic
learning process in the scene text recognition. Different from previous methods considering …

Text recognition has attracted considerable research interests because of its various
applications. The cutting-edge text recognition methods are based on attention mechanisms …

Scene text detection has witnessed rapid development in recent years. However, there still
exists two main challenges: 1) many methods suffer from false positives in their text …

Scene text spotting is of great importance to the computer vision community due to its wide
variety of applications. Recent methods attempt to introduce linguistic knowledge for …

Attention-based scene text recognizers have gained huge success, which leverages a more
compact intermediate representation to learn 1d-or 2d-attention by a RNN-based encoder …

Nowadays, scene text recognition has attracted more and more attention due to its various
applications. Most state-of-the-art methods adopt an encoder-decoder framework with …

In this paper, we are interested in editing text in natural images, which aims to replace or
modify a word in the source image with another one while maintaining its realistic look. This …

The exploration of linguistic information promotes the development of scene text recognition
task. Benefiting from the significance in parallel reasoning and global relationship capture …