SOTAVerified

Denoising

Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.

( Image credit: Beyond a Gaussian Denoiser )

Papers

Showing 10011010 of 7282 papers

TitleStatusHype
Generalized Low Rank ModelsCode1
A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising ModelsCode1
gDDIM: Generalized denoising diffusion implicit modelsCode1
Masked Autoencoders as Image ProcessorsCode1
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and GenerationCode1
Masked Diffusion as Self-supervised Representation LearnerCode1
A Conditional Diffusion Model for Electrical Impedance Tomography Image ReconstructionCode1
Burst Denoising of Dark ImagesCode1
End-to-End Diffusion Latent Optimization Improves Classifier GuidanceCode1
CrackSegDiff: Diffusion Probability Model-based Multi-modal Crack SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified