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 4601–4610 of 7282 papers

TitleStatusHype
Watch Your Steps: Local Image and Scene Editing by Text Instructions—0
L0TV: A New Method for Image Restoration in the Presence of Impulse Noise—0
A Denoising Loss Bound for Neural Network based Universal Discrete Denoisers—0
Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Images—0
Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Faces—0
Label Denoising through Cross-Model Agreement—0
Label Denoising with Large Ensembles of Heterogeneous Neural Networks—0
TIER-A: Denoising Learning Framework for Information Extraction—0
Label-efficient Multi-organ Segmentation Method with Diffusion Model—0
Watermarking in Diffusion Model: Gaussian Shading with Exact Diffusion Inversion via Coupled Transformations (EDICT)—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