Research map / Image generation / Autoregressive and latent generation
A-Lamp: Adaptive Layout-Aware Multi-Patch Deep Convolutional Neural Network for Photo Aesthetic Assessment
Check your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use adaptive salient, diverse, low-overlap patches instead of random crops (ablation) | VGG16 multi-patch network · AVA test | accuracy: 74.8% -> 81.7% | Helped |
| Add the layout-aware attribute-graph subnet to New-MP-Net (ablation) | New-MP-Net · AVA test | accuracy: 81.7% -> 82.5 % | Helped |
| Replace MNA-CNN average aggregation with scene attributes (ablation) | MNA-CNN · AVA test | accuracy: 77.1 % -> 77.4 % | No clear effect |
| Use adaptive multi-patch learning instead of center-cropped single-image input | VGG16 · AVA test | accuracy: 72.2 % -> 81.7% | Helped |
| Use adaptive multi-patch learning instead of warped single-image input | VGG16 · AVA test | accuracy: 74.1 % -> 81.7% | Helped |
| Use adaptive multi-patch learning instead of padded single-image input | VGG16 · AVA test | accuracy: 72.9 % -> 81.7% | Helped |
| Use max and mean statistical aggregation rather than min, max, mean, and median (ablation) | Multi-Patch subnet · AVA test | accuracy | Helped |
| Use max and min statistical aggregation instead of other tested aggregation functions (ablation) | Multi-Patch subnet · AVA test | accuracy | Helped |
Closest papers by meaning
- Composition-Preserving Deep Photo Aesthetics Assessment (CVPR 2016 · similarity 0.92)
- Advancing Comprehensive Aesthetic Insight with Multi-Scale Text-Guided Self-Supervised Learning (AAAI 2025 · similarity 0.86)
- Bridging Cognitive Gap: Hierarchical Description Learning for Artistic Image Aesthetics Assessment (AAAI 2026 · similarity 0.86)
- AesFA: An Aesthetic Feature-Aware Arbitrary Neural Style Transfer (AAAI 2024 · similarity 0.85)
- Charm: The Missing Piece in ViT Fine-Tuning for Image Aesthetic Assessment (CVPR 2025 · similarity 0.84)
- Unlocking the Essence of Beauty: Advanced Aesthetic Reasoning with Relative-Absolute Policy Optimization (ICLR 2026 · similarity 0.84)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.