Structural health monitoring at local and global levels using computer vision technologies
has gained much attention in the structural health monitoring community in research and …

Siamese network based trackers formulate tracking as convolutional feature cross-
correlation between target template and searching region. However, Siamese trackers still …

Recently, Siamese networks have drawn great attention in visual tracking community
because of their balanced accuracy and speed. However, features used in most Siamese …

The feature models used by existing Thermal InfraRed (TIR) tracking methods are usually
learned from RGB images due to the lack of a large-scale TIR image training dataset …

Existing deep Thermal InfraRed (TIR) trackers only use semantic features to represent the
TIR object, which lack the sufficient discriminative capacity for handling distractors. This …

Although numerous recent tracking approaches have made tremendous advances in the
last decade, achieving high-performance visual tracking remains a challenge. In this paper …

In this paper, we propose a progressive unsupervised learning (PUL) framework, which
entirely removes the need for annotated training videos in visual tracking. Specifically, we …

Abstract Existing deep Thermal InfraRed (TIR) trackers usually use the feature models of
RGB trackers for representation. However, these feature models learned on RGB images …

Siamese network based trackers develop rapidly in the field of visual object tracking in
recent years. The majority of Siamese network based trackers now in use treat each channel …

Existing trackers usually exploit robust features or online updating mechanisms to deal with
target variations which is a key challenge in visual tracking. However, the features being …