In recent years, the dominant paradigm for text spotting is to combine the tasks of text
detection and recognition into a single end-to-end framework. Under this paradigm, both …

Scene text editing (STE) aims to replace text with the desired one while preserving
background and styles of the original text. However, due to the complicated background …

In real applications, new object classes often emerge after the detection model has been
trained on a prepared dataset with fixed classes. Fine-tuning the old model with only new …

Due to the flexible representation of arbitrary-shaped scene text and simple pipeline, bottom-
up segmentation-based methods begin to be mainstream in real-time scene text detection …

Text-based visual question answering (TextVQA), which answers a visual question by
considering both visual contents and scene texts, has attracted increasing attention recently …

Abstract Recent advanced Table Structure Recognition (TSR) models adopt image-to-text
solutions to parse table structure. These methods can be formulated as image caption …

The research focus of scene text detection and recognition has shifted to arbitrary shape text
in recent years, where the text shape representation is a fundamental problem. An ideal …

Ambiguous scene text detection is an extremely challenging task. Existing text detectors that
rely solely on visual cues often suffer from confusion due to being evenly distributed in …

Diffusion models, known for their impressive image generation abilities, have played a
pivotal role in the rise of visual text generation. Nevertheless, existing visual text generation …

Recently, generative Text-based visual question answering (TextVQA) methods, which are
often based on language models, have exhibited impressive results and drawn increasing …