Several complex networks are usually designed in salient region detection to detect saliency, which inevitably leads to very high computational and storage costs. The deep learning network has the characteristics of multi-scale and different convolution layers have different spatial resolutions，thus the design of complex network structure can be avoided. In this paper, a novel convolution neural network is designed by taking advantage of multi-scale characteristics. Both the multi-scale features and the influence of the size of salient regions are considered to saliency detection. Experiments show the superiority of our method on popular benchmark datasets.