RGB T Tracking

RGB-T tracking aims to robustly track objects using both visible (RGB) and thermal infrared (T) imagery, leveraging the complementary strengths of each modality to overcome limitations of single-modality approaches. Current research heavily emphasizes effective fusion strategies for RGB and T data, often employing transformer-based architectures and exploring techniques like prompt learning and knowledge distillation to improve efficiency and performance. This field is significant for advancing object tracking in challenging conditions, with applications ranging from autonomous driving to surveillance and robotics, where robust target identification is crucial.