Research map / Image generation / Image restoration
PD-GAN: Probabilistic Diverse GAN for Image Inpainting
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use PD-GAN instead of PIC | Places2 diverse inpainting · Places2 | LPIPS diversity, mask region: 0.1547 -> 0.1799 | Helped |
| Use PD-GAN instead of PIC | Places2 diverse inpainting · Places2 | LPIPS diversity, full image: 0.1096 -> 0.1238 | Helped |
| Add perceptual diversity loss (ablation) | PD-GAN · Places2, mask 40-50% | LPIPS diversity: 0.1934 -> 0.2206 | Helped |
| Add perceptual diversity loss (ablation) | PD-GAN · Places2, mask 40-50% | FID: 56.55 -> 52.68 | Helped |
| Replace conventional diversity loss with perceptual diversity loss (ablation) | PD-GAN · Places2, mask 40-50% | FID: 61.55 -> 52.68 | Helped |
| Replace conventional diversity loss with perceptual diversity loss (ablation) | PD-GAN · Places2, mask 40-50% | LPIPS diversity: 0.198 -> 0.2206 | Helped |
| Add hard SPDNorm alongside soft SPDNorm (ablation) | PD-GAN · Places2, mask 40-50% | FID: 61.22 -> 52.68 | Helped |
| Add soft SPDNorm alongside hard SPDNorm (ablation) | PD-GAN · Places2, mask 40-50% | FID: 61.48 -> 52.68 | Helped |
| Replace SPDNorm with SPADE (ablation) | PD-GAN · Places2, mask 40-50% | FID: 52.68 -> 60.55 | Hurt |
Closest papers by meaning
- Image Inpainting via Iteratively Decoupled Probabilistic Modeling (ICLR 2024 · similarity 0.91)
- InOut: Diverse Image Outpainting via GAN Inversion (CVPR 2022 · similarity 0.90)
- Dual-Path Image Inpainting With Auxiliary GAN Inversion (CVPR 2022 · similarity 0.88)
- High-Resolution GAN Inversion for Degraded Images in Large Diverse Datasets (AAAI 2023 · similarity 0.87)
- WarpGAN: Warping-Guided 3D GAN Inversion with Style-Based Novel View Inpainting (NeurIPS 2025 · similarity 0.87)
- Diverse Rare Sample Generation with Pretrained GANs (AAAI 2025 · similarity 0.86)
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