Jpeg Artifact Correction On Live1 Quality 20
Métriques
PSNR
PSNR-B
SSIM
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | PSNR | PSNR-B | SSIM |
|---|---|---|---|
| implicit-dual-domain-convolutional-network | 30.04 | 30.01 | 0.882 |
| hierarchical-information-flow-for-generalized | 30.66 | - | 0.8797 |
| s-net-a-scalable-convolutional-neural-network | 29.81 | 29.79 | 0.878 |
| multi-level-wavelet-cnn-for-image-restoration | 29.80 | 29.78 | 0.877 |
| towards-flexible-blind-jpeg-artifacts-removal | 30.11 | 29.70 | 0.868 |
| memnet-a-persistent-memory-network-for-image | 29.76 | 29.75 | 0.877 |
| compression-artifacts-reduction-by-a-deep | 29.23 | 29.24 | 0.865 |
| dpw-sdnet-dual-pixel-wavelet-domain-deep-cnns | 29.59 | 29.55 | 0.874 |
| quantization-guided-jpeg-artifact-correction | 29.92 | 29.51 | 0.882 |