Detecting small or tiny objects is always a difficult and challenging issue in computer vision.
In this paper, we provide a latest and comprehensive survey of deep learning-based …

Object detection, as of one the most fundamental and challenging problems in computer
vision, has received great attention in recent years. Over the past two decades, we have …

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 on drone images with low-latency is an important but challenging task on
the resource-constrained unmanned aerial vehicle (UAV) platform. This paper investigates …

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 …

The past few years have witnessed the immense success of object detection, while current
excellent detectors struggle on tackling size-limited instances. Concretely, the well-known …

Infrared small target detection plays an important role in target warning, ground monitoring,
and flight guidance. Existing methods typically utilize local-contrast information of each pixel …

As self-driving vehicles become more prevalent, the speed and accuracy of detecting
surrounding objects through onboard sensing technology have become increasingly …

At present, the existing methods have many limitations in small target detection, such as low
accuracy, a high rate of false detection, and missed detection. This paper proposes the KPE …

Deep learning-based dense object detectors have achieved great success in the past few
years and have been applied to numerous multimedia applications such as video …