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Single Image Reflection Removal Beyond Linearity

CVPR 2019 · Image generation › Image restoration · approach: Reflection removal · 135 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use non-linear alpha-mask synthesis and train RmNetsingle-image reflection removal · Zhang et al. [31] testPSNR: 20.744 -> 21.283Helped
use non-linear alpha-mask synthesis and train RmNetsingle-image reflection removal · SIR2 testPSNR: 24.271 -> 23.707Hurt
use non-linear alpha-mask synthesis and train RmNetsingle-image reflection removal · Synthetic all typesPSNR: 19.777 -> 21.656Helped
add a reconstruction loss that recombines predicted layers with the predicted mask (ablation)RmNet · Zhang et al. [31] testPSNR: 19.029 -> 21.283Helped
add a reconstruction loss that recombines predicted layers with the predicted mask (ablation)RmNet · SIR2 testPSNR: 21.011 -> 23.707Helped
add a reconstruction loss that recombines predicted layers with the predicted mask (ablation)RmNet · Synthetic all typesPSNR: 20.274 -> 21.656Helped
add a gradient loss on the transmission layer (ablation)RmNet · Zhang et al. [31] testPSNR: 19.303 -> 21.283Helped
add a gradient loss on the transmission layer (ablation)RmNet · SIR2 testPSNR: 21.276 -> 23.707Helped
add a gradient loss on the transmission layer (ablation)RmNet · Synthetic all typesPSNR: 20.229 -> 21.656Helped
fine-tune CEILNet using the diverse synthetic dataCEILNet · Zhang et al. [31] testPSNR: 18.555 -> 16.753Hurt
fine-tune Zhang et al. [31] using the diverse synthetic dataZhang et al. [31] · SIR2 testPSNR: 24.271 -> 20.265Hurt
train using the complete pixel, gradient, and reconstruction objective instead of pixel loss only (ablation)RmNet · Synthetic all typesPSNR: 19.413 -> 21.656Helped

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