We establish that three part types are relevant for image categorization, which are all naturally shared between categories when learning a part representation for image categorization.

We present an algorithm for part selection, part sharing, and image categorization by extending the AdaBoost optimization.

We extend our joint optimization to a fusion with global image representations.

We further improve over deep convolutional networks for image categorization.