Research map / Image generation / Super-resolution
Best-Buddy GANs for Highly Detailed Image Super-resolution
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add the best-buddy loss (ablation) | Beby-GAN · Set14 | LPIPS: 0.2343 -> 0.2202 | Helped |
| add the best-buddy loss (ablation) | Beby-GAN · BSDS100 | LPIPS: 0.2514 -> 0.2385 | Helped |
| add region-aware adversarial learning (ablation) | Beby-GAN · Set14 | LPIPS: 0.2272 -> 0.2202 | Helped |
| add region-aware adversarial learning (ablation) | Beby-GAN · BSDS100 | LPIPS: 0.2469 -> 0.2385 | Helped |
| use Beby-GAN instead of RCAN | ×4 super-resolution · Set14 | PSNR: 28.97 -> 26.96 | Hurt |
| use Beby-GAN instead of ESRGAN | ×4 super-resolution · Set14 | LPIPS: 0.2372 -> 0.2202 | Helped |
| use Beby-GAN-PI instead of RankSRGAN | ×4 super-resolution · Set14 | PI: 2.61 -> 2.57 | Helped |
| use Beby-GAN-PI instead of ESRGAN-PI | ×4 super-resolution · DIV2K | PI: 2.95 -> 3.02 | Hurt |
Closest papers by meaning
- Uncertainty-Aware GAN for Single Image Super Resolution (AAAI 2024 · similarity 0.90)
- GSDD: Generative Space Dataset Distillation for Image Super-resolution (AAAI 2024 · similarity 0.88)
- SeD: Semantic-Aware Discriminator for Image Super-Resolution (CVPR 2024 · similarity 0.88)
- Noise-Started One-Step Image Super-Resolution via LR-Conditioned SplitMeanFlow and GAN Refinement (NeurIPS 2026 · similarity 0.87)
- Adversarial Diffusion Compression for Real-World Image Super-Resolution (CVPR 2025 · similarity 0.87)
- Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts (CVPR 2024 · similarity 0.87)
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