Jpeg Artifact Correction On Classic5 Quality
평가 지표
PSNR
SSIM
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | PSNR | SSIM | Paper Title | Repository |
|---|---|---|---|---|
| Residual Dense Network + | 30.03 | 0.8194 | Residual Dense Network for Image Restoration | |
| FBCNN | 30.12 | 0.822 | Towards Flexible Blind JPEG Artifacts Removal | |
| MWCNN | 30.01 | - | Multi-level Wavelet-CNN for Image Restoration | |
| QGAC | 29.84 | 0.837 | Quantization Guided JPEG Artifact Correction | |
| MemNet | 29.69 | - | MemNet: A Persistent Memory Network for Image Restoration | |
| Hi-IR | 30.38 | 0.8266 | Hierarchical Information Flow for Generalized Efficient Image Restoration | - |
| DnCNN-3 | 29.4 | - | Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising |
0 of 7 row(s) selected.