{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T10:45:06Z","timestamp":1783421106443,"version":"3.54.6"},"reference-count":45,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2018,10,23]],"date-time":"2018-10-23T00:00:00Z","timestamp":1540252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NWO","award":["628.007.004"],"award-info":[{"award-number":["628.007.004"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2018,11,30]]},"abstract":"<jats:p>Baselines are the starting point of any quantitative multimedia research, and benchmarks are essential for pushing those baselines further. In this article, we present baselines for the artistic domain with a new benchmark dataset featuring over 2 million images with rich structured metadata dubbed OmniArt. OmniArt contains annotations for dozens of attribute types and features semantic context information through concepts, IconClass labels, color information, and (limited) object-level bounding boxes. For our dataset we establish and present baseline scores on multiple tasks such as artist attribution, creation period estimation, type, style, and school prediction. In addition to our metadata related experiments, we explore the color spaces of art through different types and evaluate a transfer learning object recognition pipeline.<\/jats:p>","DOI":"10.1145\/3273022","type":"journal-article","created":{"date-parts":[[2018,10,23]],"date-time":"2018-10-23T12:16:16Z","timestamp":1540296976000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":63,"title":["OmniArt"],"prefix":"10.1145","volume":"14","author":[{"given":"Gjorgji","family":"Strezoski","sequence":"first","affiliation":[{"name":"Informatics Institute, University of Amsterdam, Science Park, Amsterdam, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcel","family":"Worring","sequence":"additional","affiliation":[{"name":"Informatics Institute, University of Amsterdam, Science Park, Amsterdam, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2018,10,23]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Working Notes Proceedings of the MediaEval 2014 Workshop. http:\/\/ceurws.org\/Vol1263\/mediaeval2014_submission_35","author":"Anguera Xavier","year":"2014","unstructured":"Xavier Anguera , Luis Javier Rodr\u00edguez-Fuentes , Igor Sz\u00f6ke , Andi Buzo , and Florian Metze . 2014 . 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