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Underwater Ranker: Learn Which Is Better and How to Be Better

AAAI 2023 · Image generation › Image restoration · approach: Image harmonization and color transformation · 200 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add pre-trained URanker lossWaterNet · UIEBPSNR: 21.814 -> 21.926Helped
add pre-trained URanker lossWaterNet · UIEBSSIM: 0.9194 -> 0.9244Helped
add pre-trained URanker lossUcolor · UIEBPSNR: 20.433 -> 20.686Helped
add pre-trained URanker lossUcolor · UIEBSSIM: 0.8963 -> 0.8987Helped
add pre-trained URanker lossNU²Net · UIEBPSNR: 22.419 -> 22.669Helped
add pre-trained URanker lossNU²Net · UIEBSSIM: 0.9227 -> 0.9246Helped
add histogram prior module (ablation)URanker · URankerSet testSRCC: 0.8585 -> 0.8655Helped
add histogram prior module (ablation)URanker · URankerSet testKRCC: 0.7381 -> 0.7402Helped
replace direct connection with dynamic connection (ablation)URanker · URankerSet testSRCC: 0.8478 -> 0.8655Helped
replace direct connection with dynamic connection (ablation)URanker · URankerSet testKRCC: 0.7219 -> 0.7402Helped
replace neighbour connection with dynamic connection (ablation)URanker · URankerSet testSRCC: 0.8589 -> 0.8655Helped
replace neighbour connection with dynamic connection (ablation)URanker · URankerSet testKRCC: 0.7363 -> 0.7402Helped

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