of 197 classes and 16,185 images, represents an order of magnitude increase in size over
the only existing fine-grained car dataset [7](14 classes, 1,904 images) and is comparable in
size to the largest fine-grained datasets publicly available [9, 3]. The goals of this work are
twofold: 1) to describe the difficulties encountered when collecting such a dataset and 2) to
present baseline performance for two state-of-the-art methods.