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 …

Recently, Siamese trackers have achieved remarkable tracking performance. However,
challenges such as accurate feature representation of targets with different spatial regions …

Artificial intelligence and its derivative technologies are not only playing a role in the fields of
medicine, economy, policing, transportation, and natural science computing today but also …

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

The essence of Siamese trackers is the similarity matching between a target template deep
feature and a search region deep feature. With the successful application of the Transformer …

Visual tracking is a fundamental task in computer vision, which extracts the target context
descriptions and features from the first image frame and tracks the target in subsequent …

Siamese network-based trackers have shown remarkable success in aerial tracking. Most
previous works, however, usually perform template matching only between the initial …

Most trackers formulate visual tracking as common classification and regression (ie,
bounding box regression) tasks. Correlation features that are computed through depth-wise …

Efficient and accurate 3D multiobject tracking (MOT) is essential for autonomous driving.
However, existing methods still struggle with multiobject occlusion, in which interruptions or …