Visual Object Tracking

Visual object tracking aims to automatically locate a specific object within a video sequence across multiple frames. Current research heavily emphasizes improving the efficiency and robustness of transformer-based trackers, focusing on techniques like model compression, adaptive computation, and multimodal feature fusion to address limitations in speed and accuracy across diverse scenarios (e.g., low light, underwater, aerial). These advancements are crucial for deploying object tracking in resource-constrained environments and expanding its applications in robotics, autonomous systems, and video analysis.