Image Denoising On Dnd
Metriken
PSNR (sRGB)
SSIM (sRGB)
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | PSNR (sRGB) | SSIM (sRGB) |
|---|---|---|
| variational-denoising-network-toward-blind | 39.38 | 0.952 |
| cycleisp-real-image-restoration-via-improved | 39.56 | 0.956 |
| single-stage-adaptive-multi-attention-network | 40.05 | 0.963 |
| spatial-adaptive-network-for-single-image | 39.59 | 0.952 |
| nbnet-noise-basis-learning-for-image | 39.89 | 0.955 |
| maxim-multi-axis-mlp-for-image-processing | 39.84 | 0.954 |
| uformer-a-general-u-shaped-transformer-for | 39.98 | 0.955 |
| transfer-learning-from-synthetic-to-real-2 | 39.37 | 0.951 |
| toward-convolutional-blind-denoising-of-real | 38.06 | 0.942 |
| dualdn-dual-domain-denoising-via | 40.594 | 0.966 |
| multi-stage-progressive-image-restoration | 39.80 | 0.954 |
| learning-enriched-features-for-real-image | 39.88 | 0.956 |
| dual-adversarial-network-toward-real-world | 39.58 | 0.955 |
| restormer-efficient-transformer-for-high | 40.03 | 0.956 |
| real-image-denoising-with-feature-attention | 39.26 | 0.953 |