Understanding Aesthetics with Language: A Photo Critique Dataset for Aesthetic Assessment
Open access
Date
2022Type
- Conference Paper
ETH Bibliography
yes
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Abstract
Computational inference of aesthetics is an ill-defined task due to its subjective nature. Many datasets have been proposed to tackle the problem by providing pairs of images and aesthetic scores based on human ratings. However, humans are better at expressing their opinion, taste, and emotions by means of language rather than summarizing them in a single number. In fact, photo critiques provide much richer information as they reveal how and why users rate the aesthetics of visual stimuli. In this regard, we propose the Reddit Photo Critique Dataset (RPCD), which contains tuples of image and photo critiques. RPCD consists of 74K images and 220K comments and is collected from a Reddit community used by hobbyists and professional photographers to improve their photography skills by leveraging constructive community feedback. The proposed dataset differs from previous aesthetics datasets mainly in three aspects, namely (i) the large scale of the dataset and the extension of the comments criticizing different aspects of the image, (ii) it contains mostly UltraHD images, and (iii) it can easily be extended to new data as it is collected through an automatic pipeline. To the best of our knowledge, in this work, we propose the first attempt to estimate the aesthetic quality of visual stimuli from the critiques. To this end, we exploit the polarity of the sentiment of criticism as an indicator of aesthetic judgment. We demonstrate how sentiment polarity correlates positively with the aesthetic judgment available for two aesthetic assessment benchmarks. Finally, we experiment with several models by using the sentiment scores as a target for ranking images. Dataset and baselines are available. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000601879Publication status
publishedExternal links
Book title
Advances in Neural Information Processing Systems 35Pages / Article No.
Publisher
CurranEvent
Subject
Image aesthetic assessment; Dataset; Photo critiques; Aesthetic image captioningOrganisational unit
02154 - Media Technology Center (MTC) / Media Technology Center (MTC)
Related publications and datasets
Is new version of: https://doi.org/10.48550/arXiv.2206.08614
Notes
Presentation held on December 1, 2022More
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ETH Bibliography
yes
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