Datasets › MIT-Adobe FiveK
MIT-Adobe FiveK
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"
}
Source: https://data.csail.mit.edu/graphics/fivek/
Image source: https://data.csail.mit.edu/graphics/fivek/
Benchmarks archive 2025-07-28
All 4 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Image Enhancement | MIT-Adobe 5k | Retinexformer PSNR on sRGB 24.94 | Retinexformer: One-stage Retinex-based Transformer for... | cmhungsteve/Awesome-Transformer-Attention +4 | 11 | Compare |
| Photo Retouching | MIT-Adobe 5k | MAXIM PSNR 26.15 | MAXIM: Multi-Axis MLP for Image Processing | google-research/maxim +2 | 5 | Compare |
| Image Enhancement | MIT-Adobe FiveK | TreEnhance DeltaE 11.25 | TreEnhance: A Tree Search Method For Low-Light Image Enhancement | ocram17/treenhance | 1 | Compare |
| Low-Light Image Enhancement | MIT-Adobe FiveK | Retinexformer PSNR 24.94 | Retinexformer: One-stage Retinex-based Transformer for... | cmhungsteve/Awesome-Transformer-Attention +4 | 1 | Compare |
Papers archive 2025-07-28
14 shown of 14 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 28. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
Dataset loaders archive 2025-07-28
2 loaders as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- MIT-Adobe 5k
- MIT-Adobe FiveK
2 variant names, as the archive lists them.
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