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

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 …

With the rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …

Object detection is a well-known task in the field of computer vision, especially the small
target detection problem that has aroused great academic attention. In order to improve the …

Object detection on drone-captured scenarios is a recent popular task. As drones always
navigate in different altitudes, the object scale varies violently, which burdens the …

Recent advances in label assignment in object detection mainly seek to independently
define positive/negative training samples for each ground-truth (gt) object. In this paper, we …

We show that the YOLOv4 object detection neural network based on the CSP approach,
scales both up and down and is applicable to small and large networks while maintaining …

Most online multi-object trackers perform object detection stand-alone in a neural net without
any input from tracking. In this paper, we present a new online joint detection and tracking …

With the development of artificial intelligence technology and the popularity of intelligent
production projects, intelligent inspection systems have gradually become a hot topic in the …

Surface defect detection of products is an important process to guarantee the quality of
industrial production. A defect detection task aims to identify the specific category and …