The MIT-Adobe FiveK dataset consists of 5,000 photographs taken with SLR cameras by a set of different photographers. They are all in RAW format; that is, all the information recorded by the camera sensor is preserved. We made sure that these photographs cover a broad range of scenes, subjects, and lighting conditions. We then hired five photography students in an art school to adjust the tone of the photos. Each of them retouched all the 5,000 photos using a software dedicated to photo adjustment (Adobe Lightroom) on which they were extensively trained. We asked the retouchers to achieve visually pleasing renditions, akin to a postcard. The retouchers were compensated for their work.

This dataset was collected for our project on learning photographic adjustments. When using images from this dataset, please cite this dataset using the following BibTeX:

@inproceedings{fivek,
    author = "Vladimir Bychkovsky and Sylvain Paris and Eric Chan and Fr{\'e}do Durand",
    title = "Learning Photographic Global Tonal Adjustment with a Database of Input / Output Image Pairs",
    booktitle = "The Twenty-Fourth IEEE Conference on Computer Vision and Pattern Recognition",
    year = "2011"
}