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Title: Learning of Art Style Using AI and Its Evaluation Based on Psychological Experiments
Authors: Cong Hung, Mai
Nakatsu, Ryohei
Tosa, Naoko  kyouindb  KAKEN_id
Kusumi, Takashi  kyouindb  KAKEN_id  orcid (unconfirmed)
Koyamada, Koji  kyouindb  KAKEN_id  orcid (unconfirmed)
Author's alias: 中津, 良平
土佐, 尚子
楠見, 孝
小山田, 耕二
Keywords: GANs
Cycle GAN
Art history
Transformation of art style
Issue Date: 2020
Publisher: Springer, Cham
Journal title: Entertainment Computing - ICEC 2020
Start page: 308
End page: 316
Abstract: GANs (Generative adversarial networks) is a new AI technology that has the capability of achieving transformation between two image sets. Using GANs we have carried out a comparison between several art sets with different art styles. We have prepared four image sets; a flower image set with Impressionism art style, one with the Western abstract art style, one with Chinese figurative art style, and one with the art style of Naoko Tosa, one of the authors. Using these four sets we have carried out a psychological experiment to evaluate the difference between these four sets. We have found that abstract drawings and figurative drawings are judged to be different, figurative drawings in West and East were judged to be similar, and Naoko Tosa’s artworks are similar to Western abstract artworks.
Description: [ICEC 2020]19th IFIP TC 14 International Conference, ICEC 2020, Xi'an, China, November 10–13, 2020, Proceedings
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12523)
Rights: This is a post-peer-review, pre-copyedit version of an article published in Entertainment Computing - ICEC 2020. The final authenticated version is available online at: The full-text file will be made open to the public on 5 January 2022 in accordance with publisher's 'Terms and Conditions for Self-Archiving'.
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
DOI(Published Version): 10.1007/978-3-030-65736-9_28
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