In recent years, the study of artificial intelligence (AI) has undergone a paradigm shift. This
has been propelled by the groundbreaking capabilities of generative models both in …

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 …

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 …

Recently visually-situated text parsing (VsTP) has experienced notable advancements
driven by the increasing demand for automated document understanding and the …

In recent years, end-to-end scene text spotting approaches are evolving to the Transformer-
based framework. While previous studies have shown the crucial importance of the intrinsic …

Structured text understanding on Visually Rich Documents (VRDs) is a crucial part of
Document Intelligence. Due to the complexity of content and layout in VRDs, structured 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 …

End-to-end scene text spotting has made significant progress due to its intrinsic synergy
between text detection and recognition. Previous methods commonly regard manual …

We present MMOCR---an open-source toolbox which provides a comprehensive pipeline for
text detection and recognition, as well as their downstream tasks such as named entity …