This paper presents two applications about representative photo selection and smart thumbnailing using the results of near-duplicate detection. For a given photo cluster, near-duplicate photo pairs are first determined, and the relationships between them are modeled by a graph. The most typical one is then automatically selected by examining the mutual relation between them. For smart thumbnailing, we determine the region-of-interest of the selected representative photo based on locally matched feature points, which is a view different from conventional saliency-based approaches. The experiments show satisfactory performance in representative selection and promising results in ROI determination.