VehiDE Dataset: New dataset for Automatic vehicle damage detection in Car insurance

In the world of auto insurance, automatic car damage identification has garnered a lot of interest. However, it is difficult for us to develop a workable model for car damage identification due to the absence of high-quality datasets that are accessible to the general public. In order to achieve this, the Vehicle Damage Detection (VehiDE) dataset, the large-scale dataset made available to the public for the purpose of segmenting and detecting visual automotive damage. This dataset comprises 13,945 high-resolution photos of damaged cars together with more than 32,000 occurrences of each damage category with detailed annotations. Statistical dataset analysis is provided together with a description of the image collecting, selection, and annotation procedures. In order to emphasize the expertise of automotive damage identification, extensive experiments on the VehiDE dataset are conducted using cutting-edge deep approaches for a variety of jobs and provide thorough analysis.