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Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2019,4,30]]},"abstract":"<jats:p>Aesthetics is a subjective concept that is likely to be perceived differently among people of different ages, genders, and cultural backgrounds. While techniques that directly compute this concept in images has seen increasing attention by the multimedia and machine-learning community, there are very few attempts at encoding the influences from the photographer\u2019s viewpoint. This work demonstrates how the aesthetic quality of photos can be better learned by accounting for the demographic background of a photographer. A new AVA-PD (Photographer Demographic) dataset is created to supplement the AVA dataset by providing photographers\u2019 age, gender and location attributes. Two deep convolutional neural network (CNN) architectures are proposed to utilize demographic information for aesthetic prediction of photos; both are shown to yield better prediction capabilities compared to most existing approaches. By leveraging on AVA-PD meta-data, we also present some additional machine-learnable tasks such as identifying the photographer and predicting photography styles from a person\u2019s gallery of photos.<\/jats:p>","DOI":"10.1145\/3328993","type":"journal-article","created":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T12:34:33Z","timestamp":1564058073000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Beauty Is in the Eye of the Beholder"],"prefix":"10.1145","volume":"15","author":[{"given":"Magzhan","family":"Kairanbay","sequence":"first","affiliation":[{"name":"Multimedia University, Cyberjaya, Selangor, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3005-4109","authenticated-orcid":false,"given":"John","family":"See","sequence":"additional","affiliation":[{"name":"Multimedia University, Cyberjaya, Selangor, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4517-0391","authenticated-orcid":false,"given":"Lai-Kuan","family":"Wong","sequence":"additional","affiliation":[{"name":"Multimedia University, Cyberjaya, Selangor, Malaysia"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the Workshop at the European Conference on Computer Vision. 71--84","author":"Bar Yaniv","year":"2014","unstructured":"Yaniv Bar, Noga Levy, and Lior Wolf. 2014. 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