The three-dimensional (3D) reconstruction technology has considerable application prospects in industrial fields such as autopilot and metauniverse. The 3D reconstruction of transparent rigid bodies exhibits some challenges owing to its complex imaging laws. This review examines the 3D reconstruction technology of transparent rigid bodies, focuses on the methods based on optimized visual hull and deep learning, discusses the principle and different optimization methods based on visual hull reconstruction, describes the RGB-D depth completion and multiview reconstruction based on deep learning, presents the current dataset of transparent objects, and finally discusses the possible development direction of the 3D reconstruction technology.