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Online-Updated High-Order Collaborative Networks for Single Image Deraining

AAAI 2022 · Image generation › Image restoration · approach: Dehazing and deraining · 27 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add bidirectional scale-content similarity mining instead of omitting BiSCSM (ablation)High-order collaborative network · Rain200HPSNR: 29.583 -> 29.985Helped
Use bidirectional mining rather than element-wise summation or 1 × 1 convolution for scale fusion (ablation)BiSCSM · Rain200HPSNR: 29.625 -> 29.985; 29.541 -> 29.985Helped
Use both Down-to-Up and Up-to-Down mining rather than either direction alone (ablation)BiSCSM · Rain200HPSNR: 29.393 -> 29.985; 29.828 -> 29.985Helped
Add positional embedding (ablation)BiSCSM · Rain200HPSNR: 29.953 -> 29.985Helped
Add both 1/2- and 1/4-scale Laplacian constraints instead of no constraints (ablation)High-order collaborative network · Rain200HPSNR: 29.824 -> 29.985Helped
Use multi-scale Laplacian constraints rather than a full-scale constraint (ablation)Multi-scale compact constraints · Rain200HPSNR: 29.970 -> 29.985Helped
Add collaborative top and middle sub-networks to the bottom sub-network (ablation)High-order collaborative network · Rain200HPSNR: 29.563 -> 29.985Helped
Train the sub-networks collaboratively rather than cascade them (ablation)High-order collaborative network · Rain200HPSNR: 29.642 -> 29.985Helped
Apply online-update learning with updated pseudo ground truth rather than direct real-world fine-tuning (ablation)Proposed deraining network · Real-world rainy imagesVisual deraining qualityHelped
Apply online-update learning to a pretrained synthetic-data deraining model (ablation)DCSFN · Real-world rainy imagesVisual deraining qualityHelped

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