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

Showing 25612570 of 7282 papers

TitleStatusHype
Grids Often Outperform Implicit Neural RepresentationsCode0
Graph topology inference benchmarks for machine learningCode0
Graph Signal Recovery Using Restricted Boltzmann MachinesCode0
Guided Image Synthesis via Initial Image Editing in Diffusion ModelCode0
A note on the evaluation of generative modelsCode0
ELMformer: Efficient Raw Image Restoration with a Locally Multiplicative TransformerCode0
Discrete Object Generation with Reversible Inductive ConstructionCode0
Graph Denoising with Framelet RegularizerCode0
CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty QuantificationCode0
Discrete Denoising Diffusion Approach to Integer FactorizationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified