DELAUNAY
Introduced by Gontier et al. in DELAUNAY: a dataset of abstract art for psychophysical and machine learning research
DELAUNAY is a dataset of abstract paintings and non-figurative art objects labelled by the artists' names. This dataset provides a middle ground between natural images and artificial patterns and can thus be used in a variety of contexts, for example to investigate the sample efficiency of humans and artificial neural networks.
The dataset comprises 11,503 images from 53 categories, i.e. artists (mean number of images per artist: 217.04; standard deviation: 58.55), along with the associated URLs. These samples are split between a training set of 9202 images and a test set of 2301 images.
Papers
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