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 3601–3610 of 7282 papers

TitleStatusHype
Denoising Diffusion Error Correction Codes—0
Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI—0
Implicit neural representations for end-to-end PET reconstruction—0
Implicit Regression in Subspace for High-Sensitivity CEST Imaging—0
Denoising Diffusion for Sampling SAT Solutions—0
End-to-End Learning for Structured Prediction Energy Networks—0
Continuous-variable Quantum Diffusion Model for State Generation and Restoration—0
IM-Portrait: Learning 3D-aware Video Diffusion for Photorealistic Talking Heads from Monocular VideosC—0
3D Wasserstein generative adversarial network with dense U-Net based discriminator for preclinical fMRI denoising—0
Inversion-Free Video Style Transfer with Trajectory Reset Attention Control and Content-Style Bridging—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