Datasets › AGIQA-1K
AGIQA-1K
AI Generated Content (AIGC) refers to any form of content, such as text, images, audio, or video, that is created with the help of artificial intelligence technology. With the flourishing development of deep learning, the efficiency of AIGC generation has increased, and AI-Generated Image (AGI) is becoming more prevalent in areas such as culture, entertainment, education, social media, etc.
Unlike Natural Scene Images (NSIs) captured from natural scenes, AGIs are directly generated from AI models. Thus, AGIs obtain some unique quality characteristics and viewers tend to evaluate the quality of AGIs from some different aspects of NSIs.
Therefore, we propose the first perceptual AGI Quality Assessment (AGIQA-1K) database, which provides 1,080 AGIs along with quality labels, including technical issues, AI artifacts, unnaturalness, discrepancy, and aesthetics as major evaluation aspects.
Benchmarks archive 2025-07-28
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Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
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License archive 2025-07-28
MIT
Modalities archive 2025-07-28
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Languages archive 2025-07-28
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Variants archive 2025-07-28
- AGIQA-1K
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