Abstract: In recent years, with the rapid development of deep learning technology, the research of person search algorithms has attracted a lot of scholars' interest. Person search is to find specific target person in images based on person detection and person re-identification tasks. In this paper, we review the recent research progress on person search task in detail. The existing methods are analyzed and summarized in terms of model network structures and loss functions. According to the two different technical routes of convolutional neural network and Transformer, the main research work of their respective representative methods is focused on. According to the traditional loss function, OIM loss function, and mixed loss function, the training loss functions used in person search are summarized. In addition, the public data sets commonly used in the field of person search are summarized, and the performances of the main algorithms on the corresponding data sets are compared and analyzed. Finally, we summarize the future research directions of person search task.