
contempArt
University of Bamberg
Osaka University
The dataset consists of 14'404 paintings made by 442 art students at 15 major art universities in Germany. By focusing on localized, contemporary art we created a unique snapshot of painting culture that may be used for scientific analysis.
Contains large-scale graph networks of Instagram connections between artists themselves and who else they are connected to. This relational data can be translated into artist-level features with algorithms such as node2vec (Grover and Leskovec 2016).
From nationality, gender and class membership to Instagram specific meta-data; the images and graphs are enriched with various information collected on the artists.
@InProceedings{Huckle2020Demographic,
author = {Nikolai Huckle and Noa Garcia and Yuta Nakashima},
title = {Demographic Influences on Contemporary Art with Unsupervised Style Embeddings},
booktitle = {Proceedings of the European Conference in Computer Vision Workshops},
year = {2020},
}