This work explores and compares the plethora of metrics for the performance evaluation of
object-detection algorithms. Average precision (AP), for instance, is a popular metric for …

Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …

In LiDAR-based 3D object detection for autonomous driving, the ratio of the object size to
input scene size is significantly smaller compared to 2D detection cases. Overlooking this …

While general object detection with deep learning has achieved great success in the past
few years, the performance and efficiency of detecting small objects are far from satisfactory …

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 …

Effective strategies to restrain COVID-19 pandemic need high attention to mitigate
negatively impacted communal health and global economy, with the brim-full horizon yet to …

In computer vision, object detection is one of most important tasks, which underpins a few
instance-level recognition tasks and many downstream applications. Recently one-stage …

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 …

In the realm of computer vision, Deep Convolutional Neural Networks (DCNNs) have
demonstrated excellent performance. Video Processing, Object Detection, Image …

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 …