Motion-Compensated Frame Interpolation (MCFI) is a technique used extensively for increasing the temporal frequency of a video sequence. In order to obtain a high quality interpolation, the motion field between frames must be wellestimated. However, many current techniques for determining the motion are prone to errors in occlusion regions, as well as regions with repetitive structure. We propose an algorithm for improving both the objective and subjective quality of MCFI by refining the motion vector field. We first utilize a Discriminant Saliency classifier to determine which regions of the motion field are most important to a human observer. These regions are refined using a multi-stage motion vector refinement which promotes motion vector candidates based on their likelihood given a local neighborhood. For regions which fall below the saliency-threshold, a frame segmentation is used to locate regions of homogeneous color and texture via Normalized Cuts. Motion vectors are promoted ...