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 121130 of 7282 papers

TitleStatusHype
Learning to See in the Extremely DarkCode2
CGVQM+D: Computer Graphics Video Quality Metric and DatasetCode2
Synthesis of discrete-continuous quantum circuits with multimodal diffusion modelsCode2
Optimal Weighted Convolution for Classification and DenosingCode2
Optimal Density Functions for Weighted Convolution in Learning ModelsCode2
EasyText: Controllable Diffusion Transformer for Multilingual Text RenderingCode2
D-AR: Diffusion via Autoregressive ModelsCode2
DiSA: Diffusion Step Annealing in Autoregressive Image GenerationCode2
Training-Free Multi-Step Audio Source SeparationCode2
Improved Immiscible Diffusion: Accelerate Diffusion Training by Reducing Its MiscibilityCode2
Show:102550
← PrevPage 13 of 729Next →

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