Stanford Cars

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


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