Vehicle Damaged Detection Using Deep Learning

Abstract

Object Detection based Vehicle Damage Detection system can potentially save insurance companies Million. In this paper we propose a Vehicle Damage Detection System based on YOLO v4. We created a dataset of damaged vehicles and annotated regions consisting of Dents, Shattered Glass, damaged tail lights and scratches. We then pre-processed the images inline with the requirements of YOLO v4 and trained the model to achieve an mAP@50 of 81.20. The system proposed in this paper surpasses all previously proposed methods and gives promising results.