Jpeg Artifact Correction On Classic5 Quality 1
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PSNR
PSNR-B
SSIM
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||||
|---|---|---|---|---|
| Hi-IR | 32.62 | - | 0.8751 | Hierarchical Information Flow for Generalized Efficient Image Restoration |
| FBCNN | 32.31 | 31.74 | 0.872 | Towards Flexible Blind JPEG Artifacts Removal |
| Residual Dense Network + | 32.19 | - | 0.8704 | Residual Dense Network for Image Restoration |
| MWCNN | 32.16 | - | - | Multi-level Wavelet-CNN for Image Restoration |
| QGAC | 31.98 | 31.37 | 0.885 | Quantization Guided JPEG Artifact Correction |
| DnCNN-3 | 31.63 | - | - | Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising |
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