SOTAVerified

Image Restoration

Image Restoration is a family of inverse problems for obtaining a high quality image from a corrupted input image. Corruption may occur due to the image-capture process (e.g., noise, lens blur), post-processing (e.g., JPEG compression), or photography in non-ideal conditions (e.g., haze, motion blur).

Source: Blind Image Restoration without Prior Knowledge

Papers

Showing 721730 of 1459 papers

TitleStatusHype
Tilt-then-Blur or Blur-then-Tilt? Clarifying the Atmospheric Turbulence Model0
SPIRE: Semantic Prompt-Driven Image Restoration0
To Recurse or not to Recurse,a Low Dose CT Study0
Total Variation with Overlapping Group Sparsity and Lp Quasinorm for Infrared Image Deblurring under Salt-and-Pepper Noise0
Toward Efficient Deep Blind RAW Image Restoration0
Toward Interactive Modulation for Photo-Realistic Image Restoration0
Toward Moiré-Free and Detail-Preserving Demosaicking0
Towards Context-aware Convolutional Network for Image Restoration0
Towards Efficient Single Image Dehazing and Desnowing0
Towards properties of adversarial image perturbations0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72Unverified
2SRUDCAverage PSNR (dB)27.64Unverified
3RestormerAverage PSNR (dB)26.99Unverified
4WGWSNetAverage PSNR (dB)26.96Unverified
5DGUNetAverage PSNR (dB)26.92Unverified
6OKNetAverage PSNR (dB)26.33Unverified
7MIRNetAverage PSNR (dB)25.97Unverified
8PromptIRAverage PSNR (dB)25.9Unverified
9MPRNetAverage PSNR (dB)25.47Unverified
10MIRNetv2Average PSNR (dB)25.37Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42Unverified
2ESDNetPSNR22.12Unverified
#ModelMetricClaimedVerifiedStatus
1730L37Unverified