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 …

In recent times, text detection in the wild has significantly raised its ability due to tremendous
success of deep learning models. Applications of computer vision have emerged and got …

End-to-end scene text spotting has attracted great attention in recent years due to the
success of excavating the intrinsic synergy of the scene text detection and recognition …

In this paper, we present TExt Spotting TRansformers (TESTR), a generic end-to-end text
spotting framework using Transformers for text detection and recognition in the wild. TESTR …

Scene text detection and recognition has received increasing research attention. Existing
methods can be roughly categorized into two groups: character-based and segmentation …

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 …

Arbitrary shape text detection is a challenging task due to the high variety and complexity of
scenes texts. In this paper, we propose a novel unified relational reasoning graph network …

End-to-end text spotting aims to integrate scene text detection and recognition into a unified
framework. Dealing with the relationship between the two sub-tasks plays a pivotal role in …

Recent end-to-end trainable methods for scene text spotting, integrating detection and
recognition, showed much progress. However, most of the current arbitrary-shape scene text …

State-of-the-art scene text detection methods usually model the text instance with local
pixels or components from the bottom-up perspective and, therefore, are sensitive to noises …