In recent times, text detection in the wild has significantly raised its ability due to tremendous
success of deep learning models. Applications of computer vision have emerged and got …

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 …

We present an open-source toolbox, named MMRotate, which provides a coherent algorithm
framework of training, inferring, and evaluation for the popular rotated object detection …

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 …

Text in natural scene images plays a vital role in scene understanding. It contains a rich and
abundant amount of valuable semantic information useful in many applications such as …

Arbitrary-oriented objects widely appear in natural scenes, aerial photographs, remote
sensing images, etc., and thus arbitrary-oriented object detection has received considerable …

One of the main challenges for arbitrary-shaped text detection is to design a good text
instance representation that allows networks to learn diverse text geometry variances. Most …

The recent large-scale Contrastive Language-Image Pretraining (CLIP) model has shown
great potential in various downstream tasks via leveraging the pretrained vision and …

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

Recent end-to-end trainable methods for scene text spotting, integrating detection and
recognition, showed much progress. However, most of the current arbitrary-shape scene text …