Autoassociative Pyramidal Neural Network for face verification

In this paper, the face verification problem is addressed. A neural network with autoassociation memory and receptive fields based architecture is proposed. It is called AAPNet (AutoAssociative Pyramidal Neural Network). The proposed neural network integrates feature extraction and image reconstruction in the same structure. For a given recognition task, at least one instance of the AAPNet must be trained for each known class. Thus, the AAPNet outputs how similar is a given probe image to its class. The AAPNet is applied in a face verification task using thumbnail-sized faces and achieves better results when compared to state-of-the-art models.