Bounding box regression (BBR) has been widely used in object detection and instance
segmentation, which is an important step in object localization. However, most of the existing …

Although convolutional neural networks (CNNs) have achieved great success in computer
vision, this work investigates a simpler, convolution-free backbone network useful for many …

End-to-end text spotting aims to integrate scene text detection and recognition into a unified
framework. Dealing with the relationship between the two sub-tasks plays a pivotal role in …

End-to-end scene text spotting has attracted great attention in recent years due to the
success of excavating the intrinsic synergy of the scene text detection and recognition …

In recent years, end-to-end scene text spotting approaches are evolving to the Transformer-
based framework. While previous studies have shown the crucial importance of the intrinsic …

The use of drones and unmanned aerial vehicles has significantly increased in various real-
world applications such as monitoring illegal car parking, tracing vehicles, controlling traffic …

Scene text spotting is of great importance to the computer vision community due to its wide
variety of applications. Recent methods attempt to introduce linguistic knowledge for …

Arbitrary-oriented object detection has been a building block for rotation sensitive tasks. We
first show that the boundary problem suffered in existing dominant regression-based rotation …

End-to-end scene text spotting has made significant progress due to its intrinsic synergy
between text detection and recognition. Previous methods commonly regard manual …

A large number of annotated training images is crucial for training successful scene text
recognition models. However, collecting sufficient datasets can be a labor-intensive and …