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 13111320 of 7282 papers

TitleStatusHype
Adversarial Distortion Learning for Medical Image DenoisingCode1
Joint-Modal Label Denoising for Weakly-Supervised Audio-Visual Video ParsingCode1
Less is More: Reweighting Important Spectral Graph Features for RecommendationCode1
Gabor is Enough: Interpretable Deep Denoising with a Gabor Synthesis Dictionary PriorCode1
Learn from Unpaired Data for Image Restoration: A Variational Bayes ApproachCode1
Self-supervised Learning for Sonar Image ClassificationCode1
HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising PackageCode1
Self-Guided Learning to Denoise for Robust RecommendationCode1
ULF: Unsupervised Labeling Function Correction using Cross-Validation for Weak SupervisionCode1
BEHM-GAN: Bandwidth Extension of Historical Music using Generative Adversarial NetworksCode1
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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