Abstract
We propose a unified approach to three tasks of aesthetic score regression, binary aesthetic classification, and personalized aesthetics. First, we develop a comparator to estimate the ratio of aesthetic scores for two images. Then, we construct a pairwise comparison matrix for multiple reference images and an input image, and predict the aesthetic score of the input via the eigenvalue decomposition of the matrix. By varying the reference images, the proposed algorithm can be used for binary aesthetic classification and personalized aesthetics, as well as generic score regression. Experimental results demonstrate that the proposed unified algorithm provides the state-of-the-art performances in all three tasks of image aesthetics.
Original language | English |
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Title of host publication | Proceedings - 2019 International Conference on Computer Vision, ICCV 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1191-1200 |
Number of pages | 10 |
ISBN (Electronic) | 9781728148038 |
DOIs | |
Publication status | Published - 2019 Oct |
Event | 17th IEEE/CVF International Conference on Computer Vision, ICCV 2019 - Seoul, Korea, Republic of Duration: 2019 Oct 27 → 2019 Nov 2 |
Publication series
Name | Proceedings of the IEEE International Conference on Computer Vision |
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ISSN (Print) | 1550-5499 |
Conference
Conference | 17th IEEE/CVF International Conference on Computer Vision, ICCV 2019 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 19/10/27 → 19/11/2 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition