Papers › Image Composition Assessment with Saliency-augmented Multi-pattern Pooling
Image Composition Assessment with Saliency-augmented Multi-pattern Pooling
Bo Zhang, Li Niu, Liqing Zhang
Image composition assessment is crucial in aesthetic assessment, which aims to assess the overall composition quality of a given image. However, to the best of our knowledge, there is neither dataset nor method specifically proposed for this task. In this paper, we contribute the first composition assessment dataset CADB with composition scores for each image provided by multiple professional raters. Besides, we propose a composition assessment network SAMP-Net with a novel Saliency-Augmented Multi-pattern Pooling (SAMP) module, which analyses visual layout from the perspectives of multiple composition patterns. We also leverage composition-relevant attributes to further boost the performance, and extend Earth Mover's Distance (EMD) loss to weighted EMD loss to eliminate the content bias. The experimental results show that our SAMP-Net can perform more favorably than previous aesthetic assessment approaches.
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Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Aesthetics Quality Assessment | CADB | SAMP-Net (Ours) | EMD | 0.1798 | #1 of 1 | Archive leaderboard | report |
| Aesthetics Quality Assessment | CADB | SAMP-Net (Ours) | LCCAll | 0.6709 | #1 of 1 | Archive leaderboard | report |
| Aesthetics Quality Assessment | CADB | SAMP-Net (Ours) | MSE | 0.3867 | #1 of 1 | Archive leaderboard | report |
| Aesthetics Quality Assessment | CADB | SAMP-Net (Ours) | SRCC | 0.6564 | #1 of 1 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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