In recent years, object detection algorithms have undergone a further development and improvement, resulting in a wider range of application scenarios. As one of the most fundamental and challenging issues in the field of computer vision, the application of object detection in the field of security has also received considerable attention. Terahertz (THz) imaging which is widely used in this area because of the ability to detect hidden objects, as a type of electromagnetic wave imaging with poor imaging performance and low resolution, traditional target detection methods cannot achieve high robustness and effectiveness simultaneously. However, anyway in this possible application scenario, many possible ideas and algorithms have been proposed. This paper analyzes the possibility of applying different object detection methods to terahertz images and analyzes the existing problems in order to give the learner some basic idea and future direction. Several detectors are covered, including the traditional object detection methods and the algorithms based on Convolutional Neural Network(CNN) framework.