A 3D Object Detection Framework for Intelligent Driving using YOLOv4

As the continuous evolution of the vehicles' industry, the self-driving technology has become an indispensable part in today's intelligent vehicles. While 3D object detection is the most core technique in the self-driving technology. A little improvement in the accuracy and efficiency of a 3D object detector will be of the utmost importance to intelligent driving and human life. So this paper focused on the improvement of detecting accuracy based on the yolov4, which is also an effective object detection network. This work transformed yolov4 from a 2D detector into a 3D detector, and also improved the original yolov4 neural network with the CSPDarknet53 backbone network. The proposed framework has a more effective and accurate performance in the 3D object detecting for intelligent driving.