Single Image Deraining On Test2800
Métriques
PSNR
SSIM
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | PSNR | SSIM |
|---|---|---|
| multi-stage-progressive-image-restoration | 33.64 | 0.938 |
| uncertainty-guided-multi-scale-residual-1 | 29.97 | 0.905 |
| recurrent-squeeze-and-excitation-context | 31.29 | 0.904 |
| multi-scale-progressive-fusion-network-for | 32.82 | 0.930 |
| restormer-efficient-transformer-for-high | 34.18 | 0.944 |
| progressive-image-deraining-networks-a-better | - | 0.916 |
| semi-supervised-cnn-for-single-image-rain | 24.43 | 0.782 |
| density-aware-single-image-de-raining-using-a | 28.13 | 0.867 |
| kbnet-kernel-basis-network-for-image | 34.19 | 0.944 |
| maxim-multi-axis-mlp-for-image-processing | 33.80 | - |
| clearing-the-skies-a-deep-network | 24.31 | 0.861 |
| hinet-half-instance-normalization-network-for | 33.91 | 0.941 |