Fine-Grained Vehicle Classification

Vehicle-Rear is a novel dataset for vehicle identification that contains more than three hours of high-resolution videos, with accurate information about the make, model, color and year of nearly 3,000 vehicles, in addition to the position and identification of their license plates.

The UFPR-VCR dataset contains 10,039 images of 9,502 distinct vehicles across various categories, including cars, vans, buses, and trucks. The images capture a broad spectrum of real-world conditions, such as frontal and rear views, partial occlusions, diverse lighting situations, and nighttime scenes. The dataset was designed to address Vehicle Color Recognition (VCR) in more challenging scenarios than those explored in previous studies.