Datasets › CSIQ

CSIQ (Categorical Subjective Image Quality)

Introduced by Eric C. Larson et al. in Most Apparent Distortion: Full-Reference Image Quality Assessment and the Role of Strategy1 Jan 2010 archive 2025-07-28

The CSIQ database consists of 30 original images, each is distorted using six different types of distortions at four to five different levels of distortion. CSIQ images are subjectively rated base on a linear displacement of the images across four calibrated LCD monitors placed side by side with equal viewing distance to the observer. The database contains 5000 subjective ratings from 35 different observers, and ratings are reported in the form of DMOS.

Benchmarks archive 2025-07-28

All 1 leaderboard 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)PaperCode
No-Reference Image Quality Assessment CSIQ UNIQA SRCC 0.964 You Only Train Once: A Unified Framework for Both... barcodereader/yoto 8 Compare

Papers archive 2025-07-28

8 shown of 8 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 115. 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

No loader listed in the archive.

Tasks archive 2025-07-28

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

  • CSIQ

1 variant name, as the archive lists them.

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