The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
AVA: A large-scale database for aesthetic visual analysis
Abstract
With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks.
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(2007) · CaltechAUTHORS (California Institute of Technology) · Cited by 2,274
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Self-citationStudying Aesthetics in Photographic Images Using a Computational Approach
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“Next, we trained a CLIP linear probe to predict human aesthetic judgments using the AVA dataset [33] (Appendix A).”
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Exploring CLIP for Assessing the Look and Feel of Images
Wang, J., Chan, K. C. K., & Loy, C. C. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i2.25353 · Cited by 733
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Metadata
- Authors
- Murray, N., Marchesotti, L., & Perronnin, F.
- Venue
- 2012 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2012-06
- Pages
- 2408-2415
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2078807908
- Cited by
- 936
- References
- 19
- FWCI
- 44.66
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Murray, N., Marchesotti, L., & Perronnin, F. (2012). AVA: A large-scale database for aesthetic visual analysis. 2012 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2012.6247954
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