With the rise and development of deep learning, computer vision has been tremendously
transformed and reshaped. As an important research area in computer vision, scene text …

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 …

Context-aware STR methods typically use internal autoregressive (AR) language models
(LM). Inherent limitations of AR models motivated two-stage methods which employ an …

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 …

Many new proposals for scene text recognition (STR) models have been introduced in
recent years. While each claim to have pushed the boundary of the technology, a holistic …

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 …

Recently, models based on deep neural networks have dominated the fields of scene text
detection and recognition. In this paper, we investigate the problem of scene text spotting …

Automated recognition of texts in scenes has been a research challenge for years, largely
due to the arbitrary text appearance variation in perspective distortion, text line curvature …

Irregular text is widely used. However, it is considerably difficult to recognize because of its
various shapes and distorted patterns. In this paper, we thus propose a multi-object rectified …