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Learned Color Constancy From Local Correspondences AbstractHuman color constancy, the ability to correct for color deviation caused by illumination changes, is still unmatched by computer vision performances. The approach taken in this paper learns how illumination changes affect reference objects. It can then explain complex non-linear color transformations with only a few parameters. Global color changes can consequently be estimated from several observations of small reference regions.
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