DeepFeat: A Bottom Up and Top Down Saliency Model Based on Deep Features of Convolutional Neural Nets

Understand

A deep feature based saliency model (DeepFeat) is developed to leverage the understanding of the prediction of human fixations.

• Traditional saliency models often predict the human visual attention relying on few level image cues.
• Although such models predict fixations on a variety of image complexities, their approaches are limited to the incorporated features.
• In this study, we aim to provide an intuitive interpretation of convolu- tional neural network deep features by combining low and high level visual factors.