mlsanityData to 7 Oct 2026

Image Composition Assessment with Saliency-augmented Multi-pattern Pooling

arXiv 2104.03133 ↗First posted 7 Apr 2021cs.CVcited by 21

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Abstract (arXiv)

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.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 22 of its 68 references that are in the map. First posted on arXiv 7 Apr 2021.

Builds on

22 of 68 references.

References · 22

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10 more
  1. 2016Squared Earth Mover's Distance-based Loss for Training Deep Neural Networkscited by 45
  2. 2017A-Lamp: Adaptive Layout-Aware Multi-Patch Deep Convolutional Neural Network for Photo Aesthetic Assessmentcited by 28
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  5. 2019Image Cropping with Composition and Saliency Aware Aesthetic Score Mapcited by 20
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 3; 2024: 4; 2025: 4; 2026: 7.

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  1. 2022Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectivescited by 314
  2. 2021Making Images Real Again: A Comprehensive Survey on Deep Image Compositioncited by 63
  3. 2023Towards Explainable In-the-Wild Video Quality Assessment: A Database and a Language-Prompted Approachcited by 45
  4. 2023DreamEdit: Subject-driven Image Editingcited by 37
  5. 2022Best Prompts for Text-to-Image Models and How to Find Themcited by 35
  6. 2025JarvisEvo: Towards a Self-Evolving Photo Editing Agent with Synergistic Editor-Evaluator Optimizationcited by 30
  7. 2023X-IQE: eXplainable Image Quality Evaluation for Text-to-Image Generation with Visual Large Language Modelscited by 28
  8. 2024Finding Waldo: Towards Efficient Exploration of NeRF Scene Spacescited by 8
  9. 2025PhotoFramer: Multi-modal Image Composition Instructioncited by 8
  10. 2025Semantic to Structure: Learning Structural Representations for Infringement Detectioncited by 4
  11. 2024Self-supervised Photographic Image Layout Representation Learningcited by 3
  12. 20243D View Optimization for Improving Image Aestheticscited by 1
9 more
  1. 2024AID-AppEAL: Automatic Image Dataset and Algorithm for Content Appeal Enhancement and Assessment Labelingcited by 1
  2. 2026Aesthetic Camera Viewpoint Suggestion with 3D Aesthetic Fieldcited by 1
  3. 2025Explaining Automatic Image Assessmentcited by 0
  4. 2026Semantically Stable Image Composition Analysis via Saliency and Gradient Vector Flow Fusioncited by 0
  5. 2026Progressive Photorealistic Simplificationcited by 0
  6. 2026CROP: Expert-Aligned Image Cropping via Compositional Reasoning and Optimizing Preferencecited by 0
  7. 2026COMPASS: Grounding Composition-Intent Guidance in Unified Multimodal Modelscited by 0
  8. 2026Learning visual representations for compositional analysis of artworks and photographscited by 0
  9. 2026Discrete Annotation, Continuous Preference: Rethinking Supervision for Accurate and Generalizable Aesthetic Image Croppingcited by 0