Noise Estimation On Sidd
Métriques
Average KL Divergence
PSNR Gap
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Average KL Divergence | PSNR Gap | Paper Title | Repository |
|---|---|---|---|---|
| GRDN | 0.443 | 2.28 | GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling | |
| CBDNet | 0.728 | 8.30 | Toward Convolutional Blind Denoising of Real Photographs | |
| PNGAN | 0.153 | 0.84 | Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training | |
| ULRD | 0.545 | 4.90 | Unprocessing Images for Learned Raw Denoising | |
| DANet | 0.212 | 2.06 | Dual Adversarial Network: Toward Real-world Noise Removal and Noise Generation |
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