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

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Showing 311–320 of 1459 papers

TitleStatusHype
UniProcessor: A Text-induced Unified Low-level Image ProcessorCode1
Inverse Problems with Diffusion Models: A MAP Estimation PerspectiveCode0
Multi-Expert Adaptive Selection: Task-Balancing for All-in-One Image RestorationCode1
Dilated Strip Attention Network for Image Restoration—0
RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models—0
CLII: Visual-Text Inpainting via Cross-Modal Predictive Interaction—0
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
Dual High-Order Total Variation Model for Underwater Image RestorationCode0
Deep Learning CT Image Restoration using System Blur and Noise Models—0
GroupCDL: Interpretable Denoising and Compressed Sensing MRI via Learned Group-Sparsity and Circulant AttentionCode1
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All datasetsCDD-11UHDM.

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72—Unverified
2SRUDCAverage PSNR (dB)27.64—Unverified
3RestormerAverage PSNR (dB)26.99—Unverified
4WGWSNetAverage PSNR (dB)26.96—Unverified
5DGUNetAverage PSNR (dB)26.92—Unverified
6OKNetAverage PSNR (dB)26.33—Unverified
7MIRNetAverage PSNR (dB)25.97—Unverified
8PromptIRAverage PSNR (dB)25.9—Unverified
9MPRNetAverage PSNR (dB)25.47—Unverified
10MIRNetv2Average PSNR (dB)25.37—Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42—Unverified
2ESDNetPSNR22.12—Unverified
#ModelMetricClaimedVerifiedStatus
1730L37—Unverified