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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–425 of 1459 papers

TitleStatusHype
Burst Image Restoration and EnhancementCode1
LIR: A Lightweight Baseline for Image RestorationCode1
Burstormer: Burst Image Restoration and Enhancement TransformerCode1
Are Deep Neural Architectures Losing Information? Invertibility Is IndispensableCode1
PromptCIR: Blind Compressed Image Restoration with Prompt LearningCode1
Early Exit or Not: Resource-Efficient Blind Quality Enhancement for Compressed ImagesCode1
EDPN: Enhanced Deep Pyramid Network for Blurry Image RestorationCode1
On the Posterior Distribution in Denoising: Application to Uncertainty QuantificationCode1
Attention-Guided Low-Rank Tensor CompletionCode1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasksCode1
Attention Cube Network for Image RestorationCode1
A Mountain-Shaped Single-Stage Network for Accurate Image RestorationCode1
Masked Face Inpainting Through Residual Attention UNetCode1
Divide-and-Conquer Posterior Sampling for Denoising Diffusion PriorsCode1
PD-GAN: Probabilistic Diverse GAN for Image InpaintingCode1
Dual Pixel Exploration: Simultaneous Depth Estimation and Image RestorationCode1
DnSwin: Toward Real-World Denoising via Continuous Wavelet Sliding-TransformerCode1
Equipping Diffusion Models with Differentiable Spatial Entropy for Low-Light Image EnhancementCode1
Event-Based Fusion for Motion Deblurring with Cross-modal AttentionCode1
Memory augment is All You Need for image restorationCode1
LayeredDoc: Domain Adaptive Document Restoration with a Layer Separation ApproachCode1
Strip Attention for Image RestorationCode1
Dynamic Attentive Graph Learning for Image RestorationCode1
Chain-of-Restoration: Multi-Task Image Restoration Models are Zero-Shot Step-by-Step Universal Image RestorersCode1
A Comparative Study of Image Restoration Networks for General Backbone Network DesignCode1
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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