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 141150 of 7282 papers

TitleStatusHype
DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup TablesCode2
Dual-domain strip attention for image restorationCode2
A Geometric Perspective on Diffusion ModelsCode2
Diffusion Probabilistic Models beat GANs on Medical ImagesCode2
Spatio-Temporal Few-Shot Learning via Diffusive Neural Network GenerationCode2
Augraphy: A Data Augmentation Library for Document ImagesCode2
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
Diffusion Recommender ModelCode2
Diffusion Models in Vision: A SurveyCode2
Diffusion models as plug-and-play priorsCode2
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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