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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2321–2330 of 7282 papers

TitleStatusHype
Deep Multi-contrast Cardiac MRI Reconstruction via vSHARP with Auxiliary Refinement Network—0
Deep MMD Gradient Flow without adversarial training—0
Background Denoising for Ptychography via Wigner Distribution Deconvolution—0
Accelerated first-order primal-dual proximal methods for linearly constrained composite convex programming—0
End-to-End Learning for Structured Prediction Energy Networks—0
Deep Metric Learning-Based Out-of-Distribution Detection with Synthetic Outlier Exposure—0
DeepMeshFlow: Content Adaptive Mesh Deformation for Robust Image Registration—0
Backdoor Attacks against Image-to-Image Networks—0
Generative Imaging and Image Processing via Generative Encoder—0
Deep Manifold Prior—0
Show:102550
← PrevPage 233 of 729Next →
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