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 771780 of 7282 papers

TitleStatusHype
EDformer: Transformer-Based Event Denoising Across Varied Noise LevelsCode1
Deep Plug-and-Play Prior for Hyperspectral Image RestorationCode1
fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functionsCode1
FlexDiT: Dynamic Token Density Control for Diffusion TransformerCode1
EEG Synthetic Data Generation Using Probabilistic Diffusion ModelsCode1
EC-Conf: An Ultra-fast Diffusion Model for Molecular Conformation Generation with Equivariant ConsistencyCode1
Controlling Latent Diffusion Using Latent CLIPCode1
Convergence Guarantees for Non-Convex Optimisation with Cauchy-Based PenaltiesCode1
AKDT: Adaptive Kernel Dilation Transformer for Effective Image DenoisingCode1
Echo from noise: synthetic ultrasound image generation using diffusion models for real image segmentationCode1
Show:102550
← PrevPage 78 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