pDisVPL: Probabilistic Discriminative Visual Part Learning for Image Classification

This work studies the discriminative mid-level visual part learning problem from a probabilistic point of view and we derive a probabilistic graphical representation called pDisVPL to explain this learning problem. Extensive experiments on image classification benchmarks demonstrate the state-of-the-art performances.