Visual information extraction (VIE) plays an important role in Document Intelligence.
Generally, it is divided into two tasks: semantic entity recognition (SER) and relation …

Document pre-trained models and grid-based models have proven to be very effective on
various tasks in Document AI. However, for the document layout analysis (DLA) task …

Current text recognition systems, including those for handwritten scripts and scene text, have
relied heavily on image synthesis and augmentation, since it is difficult to realize real-world …

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

The diversity in length constitutes a significant characteristic of text. Due to the long-tail
distribution of text lengths, most existing methods for scene text recognition (STR) only work …

Scene text images contain not only style information (font background) but also content
information (character texture). Different scene text tasks need different information but …

In this paper, we explore the potential of the Contrastive Language-Image Pretraining (CLIP)
model in scene text recognition (STR), and establish a novel Symmetrical Linguistic Feature …

Abstract Optical Character Recognition (OCR) poses a crucial challenge within the realm of
computer vision research, as it plays a pivotal role in converting vast amounts of …

Vision model have gained increasing attention due to their simplicity and efficiency in Scene
Text Recognition (STR) task. However, due to lacking the perception of linguistic knowledge …

Scene text recognition is a rapidly developing field that faces numerous challenges due to
the complexity and diversity of scene text, including complex backgrounds, diverse fonts …