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

Introduced by Hosu et al. in KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment

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.


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