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 30513060 of 7282 papers

TitleStatusHype
Estimating User Location in Social Media with Stacked Denoising Auto-encoders0
A Self-supervised Learning Method for Raman Spectroscopy based on Masked Autoencoders0
Functions with average smoothness: structure, algorithms, and learning0
Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications0
Graph Sanitation with Application to Node Classification0
Convolutional Deep Denoising Autoencoders for Radio Astronomical Images0
Fusing Sparsity with Deep Learning for Rotating Scatter Mask Gamma Imaging0
Estimating Post-OCR Denoising Complexity on Numerical Texts0
FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model0
Estimating LASSO Risk and Noise Level0
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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