Interactive graph cuts are widely used in object segmentation but with some disadvantages: 1) Manual interactions may cause inaccurate or even incorrect segmentation results and involve more interactions especially for novices. 2) In some situations, the manual interactions are infeasible. To overcome these disadvantages, we propose a novel approach, namely Saliency Cuts, to segment object from background automatically. By exploring the effects of labels to graph cuts, the so called “Professional Labels” is introduced to evaluate labels. With the aid of saliency detection, a multiresolution framework is designed to provide “Professional Labels” automatically and implement object segmentation using graph cuts. The experiments demonstrate the promising performance of Saliency Cuts.