Thermal infrared (TIR) target tracking is susceptible to occlusion and similarity interference,
which obviously affects the tracking results. To resolve this problem, we develop an Aligned …

Making full use of temporal and spatial information is critical to cope with the appearance
changes of objects in visual object tracking. However, existing methods in the tracking field …

Image aesthetics assessment (IAA) has attracted growing interest in recent years but is still
challenging due to its highly abstract nature. Nowadays, more and more people tend to …

Siamese trackers that predict a tracking box over a regular grid of feature maps based on the
sliding-window paradigm have recently drawn widespread attention in the tracking …

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 …

Pedestrian trajectory prediction is an essential component of autonomous systems and robot
navigation. Recent research has shown promising predictive performance by designing …

A memory mechanism has attracted growing popularity in tracking tasks due to the ability of
learning long-term-dependent information. However, it is very challenging for existing …

Since Vision Transformers (ViTs) are introduced into computer vision, they have developed
rapidly in a variety of visual tasks. Recently, they have been gradually applied to visual …

Visual object tracking has witnessed continuous improvements in performance, thanks to
deep CNN learning that recently emerged. More complex CNN models invariably offer better …

Target appearance and motion variations are the primary challenges in visual tracking. To
tackle these challenges, top-performing trackers commonly rely on constructing complex …