Deep learning-based algorithms have seen a massive popularity in different areas of remote
sensing image analysis over the past decade. Recently, transformer-based architectures …

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 …

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 …

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 …

Object detection is an important and challenging problem in computer vision. Although the
past decade has witnessed major advances in object detection in natural scenes, such …

Previous approaches for scene text detection have already achieved promising
performances across various benchmarks. However, they usually fall short when dealing …

Recently, segmentation-based scene text detection methods have drawn extensive attention
in the scene text detection field, because of their superiority in detecting the text instances of …

Boundary discontinuity and its inconsistency to the final detection metric have been the
bottleneck for rotating detection regression loss design. In this paper, we propose a novel …

Scene text detection methods based on neural networks have emerged recently and have
shown promising results. Previous methods trained with rigid word-level bounding boxes …

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 …