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 …

The lack of large labeled training datasets hinders the usage of deep neural network for
Thermal Infrared (TIR) tracking. Regular practice is to train a tracking network with large …

Many trackers use attention mechanisms to enhance the details of feature maps. However,
most attention mechanisms are designed based on RGB images and thus cannot be …

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 …

In thermal infrared (TIR) object tracking, the scarcity of annotated TIR image datasets
hampers the performance of deep learning-based trackers. Therefore, most trackers still only …

The popularity of unmanned aerial vehicles (UAVs) has made anti-UAV technology
increasingly urgent. Object tracking, especially in thermal infrared videos, offers a promising …

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 …

Multimodal (RGB and thermal) applications are swiftly gaining importance in the computer
vision community with advancements in self-driving cars, robotics, Internet of Things, and …

针对背景杂乱, 遮挡, 热交叉以及目标形变等复杂跟踪场景下目标跟踪算法出现性能严重退化
问题, 提出一种基于自适应标签和稀疏学习相关滤波的实时红外单目标跟踪算法. 首先 …

Aerial surveillance and tracking have gained significant traction in recent years for both
civilian applications and military reconnaissance. Disaster analysis, emergency medical …