Research map / Image generation / Image restoration
Uncertainty Guided Multi-Scale Residual Learning-Using a Cycle Spinning CNN for Single Image De-Raining
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add residual learning (RN) to the U-Net base network (ablation) | UMRL · Test-1 | PSNR: 24.25 -> 27.65 | Helped |
| Add residual learning (RN) to the U-Net base network (ablation) | UMRL · Test-2 | PSNR: 23.32 -> 25.88 | Helped |
| Add the confidence-map network (CN) to BN + RN (ablation) | UMRL · Test-1 | PSNR: 27.65 -> 29.42 | Helped |
| Add the confidence-map network (CN) to BN + RN (ablation) | UMRL · Test-2 | PSNR: 25.88 -> 26.47 | Helped |
| Add cycle spinning (ablation) | UMRL · Test-1 | PSNR: 29.42 -> 29.77 | Helped |
| Add cycle spinning (ablation) | UMRL · Test-2 | PSNR: 26.47 -> 26.67 | Helped |
| Add cycle spinning (ablation) | DDN · Test-1 | PSNR: 27.33 -> 27.52 | Helped |
| Add cycle spinning (ablation) | DDN · Test-2 | PSNR: 25.63 -> 25.90 | Helped |
| Add cycle spinning (ablation) | DID-MDN · Test-1 | PSNR: 27.95 -> 28.19 | Helped |
| Add cycle spinning (ablation) | DID-MDN · Test-2 | PSNR: 26.08 -> 26.37 | Helped |
Closest papers by meaning
- Image De-Raining via Continual Learning (CVPR 2021 · similarity 0.91)
- Density-Aware Single Image De-Raining Using a Multi-Stream Dense Network (CVPR 2018 · similarity 0.90)
- Boosting Image De-Raining via Central-Surrounding Synergistic Convolution (AAAI 2025 · similarity 0.89)
- Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains (ICLR 2024 · similarity 0.87)
- Bidirectional Multi-Scale Implicit Neural Representations for Image Deraining (CVPR 2024 · similarity 0.87)
- Towards Universal Rainy Image Restoration: Benchmark and Baseline (AAAI 2025 · similarity 0.86)
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