Introduced by Jonathan Krause et al. in 3D Object Representations for Fine-Grained Categorization
The Stanford Cars dataset consists of 196 classes of cars with a total of 16,185 images, taken from the rear. The data is divided into almost a 50-50 train/test split with 8,144 training images and 8,041 testing images. Categories are typically at the level of Make, Model, Year. The images are 360×240.
Source: View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network
