Point cloud learning has lately attracted increasing attention due to its wide applications in
many areas, such as computer vision, autonomous driving, and robotics. As a dominating …

As a fundamental task in computer vision, visual object tracking has received much attention
in recent years. Most studies focus on short-term visual tracking which addresses shorter …

Recently, Siamese trackers have gained widespread attention in visual tracking due to their
exceptional performance. However, many trackers still suffer from limitations in challenging …

Siamese-based trackers have achieved outstanding tracking performance. However, these
trackers in complex scenarios struggle to adequately integrate the valuable target feature …

The point cloud feature aggregation, which learns discriminative features from the
disordered points, plays a key role for large-scale point cloud semantic segmentation. Most …

Thermal infrared (TIR) target tracking task is not affected by illumination changes and can be
tracked at night, on rainy days, foggy days, and other extreme weather; so it is widely used in …

RGB and thermal infrared (RGBT) tracking as a solution in complex environments has
gradually become a research hotspot. The powerful complementarity between RGB and …

Although Siamese trackers have become increasingly prevalent in the visual tracking
domain, they are easily interfered by semantic distractors in complex environments, which …

Three-dimensional single object tracking (SOT) in dynamic point cloud sequences is a
fundamental problem for numerous intelligent systems. In this article, we propose a deep …

Long-term tracking is a critical and rapidly developing field in visual object tracking research.
The tracking target's appearance can change over time due to its motion or environmental …