The empowering unmanned aerial vehicles (UAVs) have been extensively used in providing
intelligence such as target tracking. In our field experiments, a pretrained convolutional …

The low reliability of feature and tracking box detection remains a problem in visual object
tracking. Currently, most discriminative correlation filter (DCF) trackers integrate multiple …

Visual target tracking is one of the most sought-after yet challenging research topics in
computer vision. Given the ill-posed nature of the problem and its popularity in a broad …

While discriminative correlation filters (DCF)-based trackers prevail in UAV tracking for their
favorable efficiency, lightweight convolutional neural network (CNN)-based trackers using …

Unmanned-aerial-vehicle (UAV)-aided target tracking has been applied in many important
practical scenarios such as target vehicle tracking missions. However, the limited …

Unmanned Aerial Vehicle (UAV) offers lots of applications in both commerce and recreation.
With this, monitoring the operation status of UAVs is crucially important. In this work, we …

Online learning has turned out to be effective for improving tracking performance. However,
it could be simply applied for classification branch, but still remains challenging to adapt to …

Convolutional neural network (CNN) models have demonstrated great success in various
computer vision tasks including image classification and object detection. However, some …

Unmanned aerial vehicle (UAV)-based visual object tracking has enabled a wide range of
applications and attracted increasing attention in the field of artificial intelligence (AI) …

The perception of drones, also known as Unmanned Aerial Vehicles (UAVs), particularly in
infrared videos, is crucial for effective anti-UAV tasks. However, existing datasets for UAV …