A Review on 3D Object Detection for Self-Driving Cars

Object detection is one of the important applications and plays a decisive role in the research related to the field of image processing, in which 3D object detection has been a challenge in the field of self-driving cars. Many research papers on 3D image detection have been published, but each has its applications and limitations. To have an overview of 3D object detection based on which suitable methods for related applications are proposed, the paper makes a survey and classification based on the image-based method, point-cloud-based method and fusion-based method. In this paper, the authors will discuss, evaluate, and classify the most recent research on 3D object recognition and detection used in the field of self-driving cars with strengths and limitations. Besides, challenges to current successful 3D objection techniques and future research suggestions are also analyzed.