Abstract: The target detection of remote sensing images is an important part of transforming massive remote sensing data into application, and the detection of ship targets in optical remote sensing images is a research hotspot of remote sensing image processing and analysis, which has important application value. The main purpose of this paper is to study various methods of ship target detection in optical remote sensing images, and to make a systematic summary of the detection methods used currently. This article focuses on the four traditional ship target detection methods based on the statistical characteristics of gray information, visual saliency, template matching, and classification learning, and the application of deep learning methods in ship target detection, and analyzes the advantages and disadvantages of various methods, and look forward to the future development of ship detection.