Datasets › KonIQ-10k

KonIQ-10k (Konstanz Image Quality 10k Database)

Introduced by Vlad Hosu et al. in KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment14 Oct 2019 archive 2025-07-28

KonIQ-10k is a large-scale IQA dataset consisting of 10,073 quality scored images. This is the first in-the-wild database aiming for ecological validity, with regard to the authenticity of distortions, the diversity of content, and quality-related indicators. Through the use of crowdsourcing, we obtained 1.2 million reliable quality ratings from 1,459 crowd workers, paving the way for more general IQA models.

Benchmarks archive 2025-07-28

All 2 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)PaperCode
Image Quality Assessment KonIQ-10k RealQA SRCC 0.948 Next Token Is Enough: Realistic Image Quality and... AMAP-ML/RealQA 4 Compare
No-Reference Image Quality Assessment KonIQ-10k RvTC (image-only) PLCC 0.95 Language Integration in Fine-Tuning Multimodal Large... — 1 Compare

Papers archive 2025-07-28

5 shown of 5 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 113. 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

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • KonIQ-10k

1 variant name, as the archive lists them.

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