When performing object tracking tasks, precisely tracking the desired target is the optimization goal of the tracking algorithm. Generally, deep learning models with larger model sizes and higher computational costs tend to have stronger computational capabilities. However, uncontrolled increases in model size and computational cost can make the algorithm difficult to use in practice. Therefore, to find a suitable balance between increasing computational cost and improving computational performance, this paper introduces a lightweight object tracking method that introduces a CNN attention mech...
