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 4711–4720 of 7282 papers

TitleStatusHype
Super-resolution Reconstruction of Single Image for Latent features—0
Learning to Kindle the StarlightCode0
N2V2 -- Fixing Noise2Void Checkerboard Artifacts with Modified Sampling Strategies and a Tweaked Network Architecture—0
CaDM: Codec-aware Diffusion Modeling for Neural-enhanced Video Streaming—0
CurvPnP: Plug-and-play Blind Image Restoration with Deep Curvature DenoiserCode0
TIER-A: Denoising Learning Framework for Information Extraction—0
A Comprehensive Survey of Transformers for Computer Vision—0
JSRNN: Joint Sampling and Reconstruction Neural Networks for High Quality Image Compressed Sensing—0
An Adapter based Multi-label Pre-training for Speech Separation and Enhancement—0
SRNR: Training neural networks for Super-Resolution MRI using Noisy high-resolution Reference data—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