Jpeg Artifact Correction On Classic5 Quality
Metrics
PSNR
SSIM
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | PSNR | SSIM |
|---|---|---|
| residual-dense-network-for-image-restoration | 30.03 | 0.8194 |
| towards-flexible-blind-jpeg-artifacts-removal | 30.12 | 0.822 |
| multi-level-wavelet-cnn-for-image-restoration | 30.01 | - |
| quantization-guided-jpeg-artifact-correction | 29.84 | 0.837 |
| memnet-a-persistent-memory-network-for-image | 29.69 | - |
| hierarchical-information-flow-for-generalized | 30.38 | 0.8266 |
| beyond-a-gaussian-denoiser-residual-learning | 29.4 | - |