Datasets › PIPAL

PIPAL (Perceptual Image Processing ALgorithms IQA Dataset)

Introduced by Jinjin Gu et al. in PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration23 Jul 2020 archive 2025-07-28

PIPAL training set contains 200 reference images, 40 distortion types, 23k distortion images, and more than one million human ratings. Especially, we include GAN-based algorithms’ outputs as a new GAN-based distortion type. We employ the Elo rating system to assign the Mean Opinion Scores (MOS).

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 37 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • PIPAL
  • PIPAL NTIRE2021 Validation Testset

2 variant names, as the archive lists them.

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