Research map / Image generation / Editing and style transfer
Blemish-Aware and Progressive Face Retouching With Limited Paired Data
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the two-stage progressive framework with blemish-aware attention | BPFRe · FFHQR All | PSNR: 44.35 -> 45.29 | Helped |
| Use the two-stage progressive framework with blemish-aware attention | BPFRe · FFHQR Hard | PSNR: 38.67 -> 38.98 | Helped |
| Add the encoder-decoder stage and AE2D (ablation) | BPFRe · FFHQR | PSNR: 40.70 -> 45.29 | Helped |
| Add the generator stage and AD2G (ablation) | BPFRe · FFHQR | PSNR: 43.80 -> 45.29 | Helped |
| Add both blemish-aware attention modules (ablation) | BPFRe · FFHQR | PSNR: 44.38 -> 45.29 | Helped |
| Add both blemish-aware attention modules (ablation) | BPFRe · FFHQR | LPIPS: 0.0101 -> 0.0092 | Helped |
Closest papers by meaning
- RetouchFormer: Semi-supervised High-Quality Face Retouching Transformer with Prior-Based Selective Self-Attention (AAAI 2024 · similarity 0.90)
- RetouchGPT: LLM-based Interactive High-Fidelity Face Retouching via Imperfection Prompting (AAAI 2025 · similarity 0.87)
- VRetouchEr: Learning Cross-frame Feature Interdependence with Imperfection Flow for Face Retouching in Videos (CVPR 2024 · similarity 0.86)
- DiffRetouch: Using Diffusion to Retouch on the Shoulder of Experts (AAAI 2025 · similarity 0.84)
- PHR-DIFF: Portrait Highlights Removal via Patch-aware Diffusion Model (AAAI 2025 · similarity 0.83)
- Self-Supervised Selective-Guided Diffusion Model for Old-Photo Face Restoration (NeurIPS 2025 · similarity 0.83)
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