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

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Showing 4721–4730 of 7282 papers

TitleStatusHype
Learning Nonlinear Spectral Filters for Color Image Reconstruction—0
Learning Non-local Image Diffusion for Image Denoising—0
Learning Personalized Representation for Inverse Problems in Medical Imaging Using Deep Neural Network—0
Learning quadrangulated patches for 3D shape parameterization and completion—0
Learning Quadrangulated Patches For 3D Shape Processing—0
Learning Representations of Affect from Speech—0
Token Caching for Diffusion Transformer Acceleration—0
Learning Robust Representations with Graph Denoising Policy Network—0
Learning robust speech representation with an articulatory-regularized variational autoencoder—0
Wavelet based multivariate signal denoising using Mahalanobis distance and EDF statistics—0
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified