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Incremental Image De-raining via Associative Memory

AAAI 2023 · Continual learning › Online and replay-based · approach: Dynamic expansion and isolation · 1 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add Associative Memory to PreNet instead of PIGWMPreNet · Rain100H (Rain100H-Rain100L)PSNR: 28.08 -> 28.84Helped
Add Associative Memory to ID-cgan instead of PIGWMID-cgan · Rain800 (Rain800-Rain100L)PSNR: 23.36 -> 24.02Helped
Add Associative Memory to ID-cgan instead of PIGWMID-cgan · Rain100H (Rain800-Rain100H)PSNR: 11.16 -> 12.87Helped
Add Associative Memory to PreNet instead of PIGWMPreNet · Rain1400 (Rain100H-Rain100L-Rain1400)PSNR: 28.06 -> 29.23Helped
Add Associative Memory to REHEN instead of PIGWMREHEN · SPA-Data testPSNR: 34.83 -> 34.93Helped
Add heuristics mapping reconstruction to SASI (ablation)SASI · Rain100H (Rain100H-Rain100L)PSNR: 19.42 -> 29.14Helped
Add heuristics mapping reconstruction to SASI (ablation)SASI · Rain100H (Rain100H-Rain100L)SSIM: 0.673 -> 0.883Helped
Add parameter isolation to heuristics-enabled SASI (ablation)SASI + Heuristics · Rain100H (Rain100H-Rain100L)PSNR: 29.14 -> 30.05Helped
Add parameter isolation to heuristics-enabled SASI (ablation)SASI + Heuristics · Rain100H (Rain100H-Rain100L)SSIM: 0.883 -> 0.911Helped

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