A combined convolutional neural network and potential region-of-interest model for saliency detection
Yu Hu, Zhen Liang, Zheru Chi, Hong Chuan Fu · 2015
A saliency detection model for approaching the human performance is a challenging research topic. In this paper, a new saliency model is proposed to detect saliency in natural scenes by using a trained convolutional neural network and a region-based validation method. The convolutional neural network (CNN) focuses on image details and local contrast of an image, while the region-based validation method focus on global information. Experimental results show that the two components of the model are complementary for each other in producing high-quality saliency maps.