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Research map / Image generation / Image restoration

Deep Image Prior

CVPR 2018 · Image generation › Image restoration · approach: Priors for restoration networks · 2,004 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
average restored images from the last optimization iterations (ablation)Deep Image Prior · Standard denoising dataset, σ = 25PSNR: 29.22 -> 30.43Helped
average the results of two optimization runs (ablation)Deep Image Prior · Standard denoising dataset, σ = 25PSNR: 30.43 -> 31.00Helped
use Deep Image Prior instead of bicubic upsampling4x super-resolution · Set5PSNR: 28.43 -> 29.90Helped
use Deep Image Prior instead of bicubic upsampling4x super-resolution · Set14PSNR: 26.05 -> 27.00Helped
use Deep Image Prior instead of trained SRResNet4x super-resolution · Set5PSNR: 32.10 -> 29.90Hurt
use Deep Image Prior instead of trained SRResNet4x super-resolution · Set14PSNR: 28.53 -> 27.00Hurt
use Deep Image Prior instead of Papyan et al.'s convolutional sparse codingInpainting · BarbaraPSNR: 28.14 -> 32.22Helped
use deeper encoder-decoder architectures (ablation)Deep Image Prior inpainting · Inpaintingvisual restoration qualityHelped
add U-Net skip connections to the ResNet architecture (ablation)Deep Image Prior inpainting · Inpaintingvisual restoration qualityHurt
increase optimization from 2400 to 50K iterations (ablation)Deep Image Prior JPEG restoration · JPEG-compressed image restorationvisual restoration qualityHurt

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