Convolutional neural networks (CNNs) are one of the main types of neural networks used for
image recognition and classification. CNNs have several uses, some of which are object …

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

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 …

In this paper, we formally address universal object detection, which aims to detect every
scene and predict every category. The dependence on human annotations, the limited …

Detecting tiny objects is a very challenging problem since a tiny object only contains a few
pixels in size. We demonstrate that state-of-the-art detectors do not produce satisfactory …

Detection of small objects and objects far away in the scene is a major challenge in
surveillance applications. Such objects are represented by small number of pixels in the …

Detecting tiny objects is one of the main obstacles hindering the development of object
detection. The performance of generic object detectors tends to drastically deteriorate on tiny …

The prevailing applications of Unmanned Aerial Vehicles (UAVs) in transportation systems
promote the development of object detection methods to collect real-time traffic information …

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 …