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Even high-quality lenses suffer from optical aberrations, especially when used at full aperture. Furthermore, there are significant lens-to-lens deviations due to manufacturing tolerances, often rendering current software solutions like DxO, Lightroom, and PTLens insufficient as they don't adapt and only include generic lens blur models. We propose a method that enables the self-calibration of lenses from a natural image, or a set of such images. To this end we develop a machine learningdoi:10.1109/iccv.2015.77 dblp:conf/iccv/HirschS15 fatcat:bvex5tdb5bgadoztz3onksooq4