As a sort of model-free tracking approach, discriminative correlation filter (DCF)-based
trackers have shown prominent performance in unmanned aerial vehicle (UAV) tracking …

Unmanned aerial vehicles (UAVs) visual tracking has always been a challenging task.
Existing correlation filter tracking algorithms typically utilize the histograms of oriented …

Object tracking is a fundamental task for the visual perception system on the intelligent
unmanned aerial vehicle (UAV). The high efficiency of correlation filter (CF) based trackers …

In long-term video object tracking (VOT) tasks, most long-term trackers are modified from
short-term trackers, which contain more and more machine learning modules to improve …

The early detection of handguns and knives from surveillance videos is crucial to enhance
people's safety. Despite the increasing development of Deep Learning (DL) methods for …

Abstract The Visual Object Tracking challenge VOT2022 is the tenth annual tracker
benchmarking activity organized by the VOT initiative. Results of 93 entries are presented; …

In a sequence, the appearance of both the target and background often changes
dramatically. Offline-trained models may not handle huge appearance variations well …

Unmanned aerial vehicle (UAV) visual tracking has been a hot research topic in the field of
remote sensing. Many filter-based UAV trackers have achieved excellent performance …

Most existing prevalent trackers draw support from deep learning networks to acquire more
effective target features, while we found that the dominant discriminative trackers employ a …

Currently, most Discriminative Correlation Filters (DCF) algorithms used for Unmanned
Aerial Vehicle (UAV) target tracking primarily focus on improving the tracking model …