SPAQ (Smartphone Photography Attribute and Quality)

Introduced by Fang et al. in Perceptual Quality Assessment of Smartphone Photography

The Smartphone Photography Attribute and Quality (SPAQ) dataset is a comprehensive database for the perceptual quality assessment of smartphone photography. It was introduced in a paper titled "Perceptual Quality Assessment of Smartphone Photography" presented at the IEEE Conference on Computer Vision and Pattern Recognition in 2020.

The SPAQ dataset consists of 11,125 pictures taken by 66 smartphones. Each image in the dataset is attached with rich annotations, including: - Image quality - Image attributes (brightness, colorfulness, contrast, noisiness, and sharpness) - Scene category labels (animal, cityscape, human, indoor scene, landscape, night scene, plant, still life, and others) - Exchangeable image file format (EXIF) data

These annotations were collected in a well-controlled laboratory environment. The dataset has been used to train blind image quality assessment (BIQA) models, providing insights into how EXIF data, image attributes, and high-level semantics interact with image quality. The SPAQ dataset and the proposed BIQA models are available on GitHub.


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