Photozilla: An Image Dataset of Photography Styles and its Application to Visual Embedding and Style Detection-Reference-Cited by-同舟云学术

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Photozilla: An Image Dataset of Photography Styles and its Application to Visual Embedding and Style Detection

Published:2023-11-06 Issue: Volume:1 Page:445-449
ISSN:
Container-title:Proceedings of the International Conference on Advances in Social Networks Analysis and Mining
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Author:

Singhal Trisha¹^ORCID,Liu Junhua¹^ORCID,Mu Wenchuan¹^ORCID,Blessing Lucienne T. M.¹^ORCID,Lim Kwan Hui¹^ORCID

Affiliation:

1. Singapore University of Technology and Design, Singapore, Singapore

Funder

Singapore University of Technology and Design

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3625007.3627476

Reference28 articles.

1. Omnicore agency https://www.omnicoreagency.com/instagram-statistics/.

2. T. Singhal, J. Liu, L. T. Blessing, and K. H. Lim, "Photozilla: A Large-Scale Photography Dataset and Visual Embedding for 20 Photography Styles," in WiCV, 2021.

3. Ava: A large-scale database for aesthetic visual analysis;Murray N.;CVPR,2012

4. S. Karayev, M. Trentacoste, H. Han, A. Agarwala, T. Darrell, A. Hertzmann, and H. Winnemoeller, "Recognizing image style," arXiv:1311.3715, 2013.

5. C. Zhang, C. Kaeser-Chen, G. Vesom, J. Choi, M. Kessler, and S. Belongie, "The imet collection 2019 challenge dataset," arXiv:1906.00901, 2019.

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