In computer vision, significant advances have been made on object detection with the rapid
development of deep convolutional neural networks (CNN). This paper provides a …

The research advances concerning the typical architectures of convolutional neural
networks (CNNs) as well as their optimizations are analyzed and elaborated in detail in this …

This paper revisits feature pyramids networks (FPN) for one-stage detectors and points out
that the success of FPN is due to its divide-and-conquer solution to the optimization problem …

DETR has been recently proposed to eliminate the need for many hand-designed
components in object detection while demonstrating good performance. However, it suffers …

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 …

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 …

High-resolution representations are essential for position-sensitive vision problems, such as
human pose estimation, semantic segmentation, and object detection. Existing state-of-the …

Abstract Model efficiency has become increasingly important in computer vision. In this
paper, we systematically study neural network architecture design choices for object …

Drone captured images have overwhelming characteristics including dramatic scale
variance, complicated background filled with distractors, and flexible viewpoints, which pose …

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 …