The process of designing an efficient tracker for thermal infrared imagery is one of the most
challenging tasks in computer vision. Although a lot of advancement has been achieved in …

Infrared object tracking is an important research field of computer vision. Existing tracking-by-
detection algorithms usually use appearance information to distinguish between the target …

Due to their resilience against lighting variations, thermal infrared (TIR) images demonstrate
robust adaptability in diverse environments, enabling effective object tracking even in …

To overcome the shortcomings of low signal-to-noise ratio and less available information of
infrared images, as well as the challenges of fast camera motion and partial occlusion, a …

To solve the problem of infrared (IR) small target tracking loss or error caused by factors
such as scale changes, motion blur, and occlusion, this article proposes a multistrategy …

Infrared object tracking is a key technology in many surveillance applications. General visual
tracking algorithms designed for color images can not handle infrared targets very well due …

Unlike the visual object tracking, thermal infrared object tracking can track a target object in
total darkness. Therefore, it has broad applications, such as in rescue and video …

In the field of automatic target recognition and tracking, long-term tracking for aerial infrared
target has been recently seen with great interest. Although deep trackers and correlation …

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 …

In recent years, visual object tracking, as a prominent research area in computer vision, has
garnered significant attention. To bolster the robustness of trackers across a spectrum of …