Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …

With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …

Object detection has been dominated by anchor-based detectors for several years.
Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal …

Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …

We present MMDetection, an object detection toolbox that contains a rich set of object
detection and instance segmentation methods as well as related components and modules …

In object detection, keypoint-based approaches often experience the drawback of a large
number of incorrect object bounding boxes, arguably due to the lack of an additional …

Recently, automatic visual data understanding from drone platforms becomes highly
demanding. To facilitate the study, the Vision Meets Drone Object Detection in Image …

Detecting objects remains one of computer vision and image understanding applications'
most fundamental and challenging aspects. Significant advances in object detection have …

Remote sensing images (RSIs) containing various ground objects have been applied in
many fields. To make semantic understanding of RSIs objective and interactive, the task …

After the revival of deep learning in computer vision in 2012, SAR ship detection comes into
the deep learning era too. The deep learning-based computer vision algorithms can work in …