Abstract: Siamese network is a coupled framework established by two or more artificial neural networks, which turns the regression problem into a similarity matching problem and has attracted much attention from researchers in the computer vision field. With the rapid development of deep learning theory, target tracking technology has been widely used in daily life. Siamese network-based target tracking algorithms have gradually replaced traditional target tracking algorithms with their relatively superior accuracy and real-time performance, becoming the mainstream algorithm for target tracking. Firstly, the challenges and traditional methods faced by target tracking tasks are introduced. Then, the basic structure and development of Siamese network are introduced, and the design principles of Siamese network-based target tracking algorithms in recent years are summarized. In addition, the performance of Siamese network-based target tracking algorithms is compared using multiple mainstream datasets for target tracking testing. Finally, the problems and prospects of Siamese network-based target tracking algorithms are proposed.

Key words: Siamese network, artificial intelligence, computer vision, visual target tracking