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 4121–4130 of 7282 papers

TitleStatusHype
Tensor Based Second Order Variational Model for Image Reconstruction—0
Guidance Free Image Editing via Explicit Conditioning—0
RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compression—0
Guided Conditional Diffusion Classifier (ConDiff) for Enhanced Prediction of Infection in Diabetic Foot Ulcers—0
Tensor denoising and completion based on ordinal observations—0
Guided Diffusion Model for Sensor Data Obfuscation—0
Tensor Denoising via Amplification and Stable Rank Methods—0
Guided Filter based Edge-preserving Image Non-blind Deconvolution—0
Guided Frequency Loss for Image Restoration—0
Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis—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