Saliency Detection via Topological Feature Modulated Deep Learning

The topological feature in an image, such as connectivity and adjacency, plays an important role in eye fixation detection. However, due to the scalar and additive nature of neurons to aggregate the node values in a local neighborhood, it is hard for convolutional neural networks (CNNs) to directly obtain and model the topological feature. Thus we adopt the topological feature which is pre-trained in accordance with the relationship between the figure and ground. Then we add a topological feature modulated convolutional layer into CNNs. By this way, the topological feature is automatically modulated by the deep features and well modeled by the CNNs. Experimental results show the proposed method surpasses the state-of-the-art by a big margin.