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 3251–3260 of 7282 papers

TitleStatusHype
BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation—0
A Machine Learning Approach for Denoising and Upsampling HRTFs—0
Adaptive Image Denoising by Targeted Databases—0
3D-Consistent Image Inpainting with Diffusion Models—0
On Probabilistic Embeddings in Optimal Dimension Reduction—0
DeGLIF for Label Noise Robust Node Classification using GNNs—0
Be Decisive: Noise-Induced Layouts for Multi-Subject Generation—0
Beamspace Channel Estimation for Wideband Millimeter-Wave MIMO: A Model-Driven Unsupervised Learning Approach—0
Alternating Phase Langevin Sampling with Implicit Denoiser Priors for Phase Retrieval—0
Deformation corrected compressed sensing (DC-CS): a novel framework for accelerated dynamic MRI—0
Show:102550
← PrevPage 326 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