Jpeg Artifact Correction On Classic5 Quality 1
Métriques
PSNR
PSNR-B
SSIM
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | PSNR | PSNR-B | SSIM |
|---|---|---|---|
| quantization-guided-jpeg-artifact-correction | 31.98 | 31.37 | 0.885 |
| multi-level-wavelet-cnn-for-image-restoration | 32.16 | - | - |
| towards-flexible-blind-jpeg-artifacts-removal | 32.31 | 31.74 | 0.872 |
| residual-dense-network-for-image-restoration | 32.19 | - | 0.8704 |
| beyond-a-gaussian-denoiser-residual-learning | 31.63 | - | - |
| hierarchical-information-flow-for-generalized | 32.62 | - | 0.8751 |