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 …

Scene text image contains two levels of contents: visual texture and semantic information.
Although the previous scene text recognition methods have made great progress over the …

The attention-based encoder-decoder framework has recently achieved impressive results
for scene text recognition, and many variants have emerged with improvements in …

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 …

Scene text recognition is a challenging task due to diverse variations of text instances in
natural scene images. Conventional methods based on CNN-RNN-CTC or encoder …

Scene text recognition (STR) is the task of recognizing character sequences in natural
scenes. While there have been great advances in STR methods, current methods which …

Pursuing accurate and robust recognizers has been a long-lasting goal for scene text
recognition (STR) researchers. Recently, attention-based methods have demonstrated their …

The transformer-based encoder-decoder framework is becoming popular in scene text
recognition, largely because it naturally integrates recognition clues from both visual and …

Text images contain both visual and linguistic information. However, existing pre-training
techniques for text recognition mainly focus on either visual representation learning or …