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 981990 of 7282 papers

TitleStatusHype
Galaxy Image Deconvolution for Weak Gravitational Lensing with Unrolled Plug-and-Play ADMMCode1
Are Diffusion Models Vision-And-Language Reasoners?Code1
Adversarial Distortion Learning for Medical Image DenoisingCode1
Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot ClassificationCode1
Are Deep Neural Architectures Losing Information? Invertibility Is IndispensableCode1
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud CompletionCode1
EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT DenoisingCode1
Low-dose CT Denoising with Language-engaged Dual-space AlignmentCode1
Fully Spiking Denoising Diffusion Implicit ModelsCode1
GAN-based Priors for Quantifying UncertaintyCode1
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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