Research map / Image generation / Autoregressive and latent generation
DoveNet: Deep Image Harmonization via Domain Verification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use DoveNet instead of S²AM | Image harmonization · All | MSE: 59.67 -> 52.36 | Helped |
| Use DoveNet instead of S²AM | Image harmonization · All | PSNR: 34.35 -> 34.75 | Helped |
| Add attention blocks (ablation) | U-Net harmonization generator · All | MSE: 68.57 -> 61.15 | Helped |
| Add attention blocks (ablation) | U-Net harmonization generator · All | PSNR: 33.16 -> 34.13 | Helped |
| Add global adversarial loss (ablation) | U-Net+att · All | MSE: 61.15 -> 55.15 | Helped |
| Add global adversarial loss (ablation) | U-Net+att · All | PSNR: 34.13 -> 34.48 | Helped |
| Add domain verification loss (ablation) | U-Net+att · All | MSE: 61.15 -> 55.00 | Helped |
| Add domain verification loss (ablation) | U-Net+att · All | PSNR: 34.13 -> 34.40 | Helped |
| Add both global adversarial and domain verification losses (ablation) | U-Net+att · All | MSE: 61.15 -> 52.36 | Helped |
| Add both global adversarial and domain verification losses (ablation) | U-Net+att · All | PSNR: 34.13 -> 34.75 | Helped |
| Use DoveNet instead of S²AM | Image harmonization on real composite images · Real composite images (99 images) | B-T score: 1.229 -> 1.437 | Helped |
Closest papers by meaning
- Deep Image Harmonization (CVPR 2017 · similarity 0.90)
- Progressive Painterly Image Harmonization from Low-Level Styles to High-Level Styles (AAAI 2024 · similarity 0.86)
- FRIH: Fine-Grained Region-Aware Image Harmonization (AAAI 2024 · similarity 0.85)
- Training-and-Prompt-Free General Painterly Harmonization via Zero-Shot Disentenglement on Style and Content References (AAAI 2025 · similarity 0.85)
- Relightful Harmonization: Lighting-aware Portrait Background Replacement (CVPR 2024 · similarity 0.83)
- Painterly Image Harmonization by Learning from Painterly Objects (AAAI 2024 · similarity 0.83)
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