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 2931–2940 of 7282 papers

TitleStatusHype
A fast patch-dictionary method for whole image recovery—0
Evolutionary Variational Optimization of Generative Models—0
EventZoom: Learning To Denoise and Super Resolve Neuromorphic Events—0
Fine-Tuning Hybrid Physics-Informed Neural Networks for Vehicle Dynamics Model Estimation—0
Convolutional Sparse Coding with Overlapping Group Norms—0
Event-Guided Denoising for Multilingual Relation Learning—0
A Set-Theoretic Study of the Relationships of Image Models and Priors for Restoration Problems—0
Fingerprinting Denoising Diffusion Probabilistic Models—0
A Tiered Move-making Algorithm for General Non-submodular Pairwise Energies—0
Generative Models for Low-Dimensional Video Representation and Compressive Sensing—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