To solve the fuzzy problem of edge information in mask results by single-stage PolarMask, a contour-point refined network is proposed herein. By predicting the angel offset and distance for each contour point, a more accurate contour can be generated. Moreover, an extra semantic segmentation is added to further refine the edge information. Experiments show that the proposed method achieves a segmentation accuracy of 32.5% on the MS COCO test dataset, 2.1 percentages higher than the fundamental PolarMask, demonstrating the effectiveness of the proposed method.