🚘 CarDD Dataset CarDD is a novel, public, large scale dataset specifically designed for vision based car damage detection and segmentation. The dataset contains 4,000 high resolution car damage images with over 9,000 well annotated instances , making it the largest public dataset of its kind. The high resolution of the images (average 684,231 pixels) is a key advantage over existing datasets that have a much lower average resolution (50,334 pixels). Higher resolution allows for more detailed annotations and the potential to detect finer damages. CarDD Dataset Overview and Features CarDD features six common external car damage categories , chosen based on frequency of occurrence and clear definitions from insurance claim statistics. 1. Dent 2. Scratch 3. Crack 4. Glass shatter 5. Tire flat 6. Lamp broken Annotation process The annotation process involved experts from the car insurance industry and trained annotators following specific guidelines based on insurance claim standards. These guidelines address challenges like • mixed damages (priority rules) • damages across components (boundary splitting) • adjacent same class damages (boundary merging). For object detection and instan…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy