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 1971–1980 of 7282 papers

TitleStatusHype
Bregman Plug-and-Play Priors—0
An Effective Image Restorer: Denoising and Luminance Adjustment for Low-photon-count Imaging—0
Analysing Diffusion Segmentation for Medical Images—0
Brick-Diffusion: Generating Long Videos with Brick-to-Wall Denoising—0
DeTrack: In-model Latent Denoising Learning for Visual Object Tracking—0
DEVDAN: Deep Evolving Denoising Autoencoder—0
Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithms—0
Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-Encoders—0
DexDiffuser: Generating Dexterous Grasps with Diffusion Models—0
Denoising Gravitational Waves using Deep Learning with Recurrent Denoising Autoencoders—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