Datasets › AGIQA-3K
AGIQA-3K
The AGIQA-3K is a fine-grained AI-generated image (AGI) subjective quality assessment database. It was created to address the need for quality models that are consistent with human subjective ratings, considering the large quality variance among different AGIs. The database extensively considers various popular AGI models, generates AGI through different prompts and model parameters, and collects subjective scores at the perceptual quality and text-to-image alignment level.
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 31 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
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- AGIQA-3K
1 variant name, as the archive lists them.
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