Jpeg Artifact Correction On Live1 Quality 20
Metriken
PSNR
PSNR-B
SSIM
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||||
|---|---|---|---|---|
| Hi-IR | 30.66 | - | 0.8797 | Hierarchical Information Flow for Generalized Efficient Image Restoration |
| FBCNN | 30.11 | 29.70 | 0.868 | Towards Flexible Blind JPEG Artifacts Removal |
| IDCN | 30.04 | 30.01 | 0.882 | Implicit Dual-domain Convolutional Network for Robust Color Image Compression Artifact Reduction |
| QGAC | 29.92 | 29.51 | 0.882 | Quantization Guided JPEG Artifact Correction |
| S-Net | 29.81 | 29.79 | 0.878 | S-Net: A Scalable Convolutional Neural Network for JPEG Compression Artifact Reduction |
| MWCNN | 29.80 | 29.78 | 0.877 | Multi-level Wavelet-CNN for Image Restoration |
| MemNet | 29.76 | 29.75 | 0.877 | MemNet: A Persistent Memory Network for Image Restoration |
| DPW-SDNet | 29.59 | 29.55 | 0.874 | DPW-SDNet: Dual Pixel-Wavelet Domain Deep CNNs for Soft Decoding of JPEG-Compressed Images |
| ARCNN | 29.23 | 29.24 | 0.865 | Compression Artifacts Reduction by a Deep Convolutional Network |
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