Learning representative and discriminative image representation by deep appearance and spatial coding
Propose a deep appearance and spatial coding model to learn image representation. Adopt stacked ISA network combined with sparse RBM to perform appearance coding. Adopt over-complete spatial max-pooling to incorporate various spatial information. Introduce a structured sparse Auto-encoder to carry out spatial coding. The experimental performances on five challenging benchmark datasets outperform baselines and related work.
image classification deep learning structured sparsity