Jpeg Artifact Correction On Classic5 Quality
评估指标
PSNR
SSIM
评测结果
各个模型在此基准测试上的表现结果
| Paper Title | Repository | |||
|---|---|---|---|---|
| Hi-IR | 30.38 | 0.8266 | Hierarchical Information Flow for Generalized Efficient Image Restoration | - |
| FBCNN | 30.12 | 0.822 | Towards Flexible Blind JPEG Artifacts Removal | |
| Residual Dense Network + | 30.03 | 0.8194 | Residual Dense Network for Image Restoration | |
| 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 | |
| DnCNN-3 | 29.4 | - | Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising |
0 of 7 row(s) selected.