Deep learning based fusion methods have been achieving promising performance in image
fusion tasks. This is attributed to the network architecture that plays a very important role in …

In recent years, correlation filter-based (CF) tracking algorithms have gained momentum in
the field of visual tracking. CF tracking algorithms have achieved compelling performance by …

RGBT tracking seeks to leverage both visible and thermal infrared images to enhance the
robustness of target tracking. This method makes up for the limitations of single-sensor …

Generative models (GMs) have received increasing research interest for their remarkable
capacity to achieve comprehensive understanding. However, their potential application in …

RGB-T Siamese trackers have drawn continuous interest in recent years due to their proper
trade-off between accuracy and speed. However, they are sensitive to the background …

Recent years have witnessed the exciting performance of trackers based on Transformer.
However, they usually separate the process of information extraction and integration …

Hyperspectral video offers a wealth of material and motion cues about objects. This
advantage proves invaluable in addressing the inherent limitations of generic RGB video …

Despite the extensive research on RGBT object tracking, there are still several challenges
and issues in practical applications, such as modality differences, lighting variations and …

In RGB-T tracking, there exist rich spatial relationships between the target and backgrounds
within multi-modal data as well as sound consistencies of spatial relationships among …

RGB-T tracking has attracted increasing attention recently due to the all-weather and all-day
working capability. However, most current RGB-T trackers usually assume that RGB data …