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 …

Dominant scene text recognition models commonly contain two building blocks, a visual
model for feature extraction and a sequence model for text transcription. This hybrid …

Scene text recognition (STR) has been an active research topic in computer vision for years.
To tackle this challenging problem, numerous innovative methods have been successively …

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 …

Abstract Existing Scene Text Recognition (STR) methods typically use a language model to
optimize the joint probability of the 1D character sequence predicted by a visual recognition …

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 …

The reading of arbitrarily-shaped text has received increasing research attention. However,
existing text spotters are mostly built on two-stage frameworks or character-based methods …

The flourishing blossom of deep learning has witnessed the rapid development of text
recognition in recent years. However, the existing text recognition methods are mainly …