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) …

This paper presents a comprehensive survey of low-light image and video enhancement,
addressing two primary challenges in the field. The first challenge is the prevalence of mixed …

Existing nighttime unmanned aerial vehicle (UAV) trackers follow an" Enhance-then-Track"
architecture-first using a light enhancer to brighten the nighttime video, then employing a …

Accurate object tracking in low-light environments is crucial, particularly in surveillance,
ethology applications, and biometric recognition systems. However, achieving this is …

The automation of unmanned aerial vehicles (UAVs) has been greatly promoted by visual
object tracking methods with onboard cameras. However, the random and complicated real …

Nighttime tracking is challenging due to the lack of sufficient training data and scene
diversity. Unsupervised domain adaptation is a solution by transferring knowledge from day …

This paper undertakes a comprehensive investigation that surpasses the conventional
examination of signal enhancement techniques and their effects on visual Simultaneous …

Visual object tracking has boosted extensive intelligent applications for unmanned aerial
vehicles (UAVs). However, the state-of-the-art (SOTA) enhancers for nighttime UAV tracking …

In view of the complexity, uncertainty, and low visibility of the night-time environment. In this
study, we designed an unsupervised domain adaptation framework, TransffCAR, using a …

Person re-identification (ReID) has gained significant interest due to growing public safety
concerns that require advanced surveillance and identification mechanisms. While most …