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 681–690 of 7282 papers

TitleStatusHype
A Fokker-Planck-Based Loss Function that Bridges Dynamics with Density Estimation—0
DiffKAN-Inpainting: KAN-based Diffusion model for brain tumor inpainting—0
Fast, Accurate Manifold Denoising by Tunneling Riemannian Optimization—0
Joint multiband deconvolution for Euclid and Vera C. Rubin images—0
Improved Diffusion-based Generative Model with Better Adversarial RobustnessCode0
AnyTop: Character Animation Diffusion with Any TopologyCode3
Rewards-based image analysis in microscopy—0
Deep unrolling for learning optimal spatially varying regularisation parameters for Total Generalised Variation—0
Generative diffusion for perceptron problems: statistical physics analysis and efficient algorithms—0
DualNeRF: Text-Driven 3D Scene Editing via Dual-Field Representation—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