Although image inpainting, or the art of repairing the old and deteriorated images, has been
around for many years, it has recently gained even more popularity, because of the recent …

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 …

Multimodal large language models (MLLMs) building upon the foundation of powerful large
language models (LLMs) have recently demonstrated exceptional capabilities in generating …

Large Vision-Language Models (LVLMs) have recently played a dominant role in
multimodal vision-language learning. Despite the great success, it lacks a holistic evaluation …

In this paper, we design and train a Generative Image-to-text Transformer, GIT, to unify
vision-language tasks such as image/video captioning and question answering. While …

Rotated object detection aims to identify and locate objects in images with arbitrary
orientation. In this scenario, the oriented directions of objects vary considerably across …

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

Text recognition is a long-standing research problem for document digitalization. Existing
approaches are usually built based on CNN for image understanding and RNN for char …

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 …

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 …