1. A method comprising: extracting, by at least one or more computing devices, visual features from images of a corpus of images; arranging, by the at least one or more computing devices, the images in clusters based at least in part on similarities of the visual features; calculating, by the at least one or more computing devices, at least two relevance features, including: first relevance features representing distribution characteristics of distances between pairs of images in a same cluster; and second relevance features representing distribution characteristics of distances between different clusters of images; and refining, by the at least one or more computing devices, the corpus by removing one or more images from the corpus based in part on the at least two relevance features to create a refined corpus.