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 3276–3300 of 7282 papers

TitleStatusHype
Deep Unfolding-Aided Parameter Tuning for Plug-and-Play-Based Video Snapshot Compressive Imaging—0
Bayesian selection for the l2-Potts model regularization parameter: 1D piecewise constant signal denoising—0
Deep Ultrasound Denoising Without Clean Data—0
Deep Ultrasound Denoising Using Diffusion Probabilistic Models—0
Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI—0
Deep Transform and Metric Learning Network: Wedding Deep Dictionary Learning and Neural Networks—0
Deep Transfer Tensor Factorization for Multi-View Learning—0
Bayesian Inference for Neighborhood Filters With Application in Denoising—0
DeepTensor: Low-Rank Tensor Decomposition with Deep Network Priors—0
Deep Stacked Networks with Residual Polishing for Image Inpainting—0
Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie—0
A Low-Cost & Real-Time Motion Capture System—0
Bayesian Formulations for Graph Spectral Denoising—0
Deep Speech Denoising with Vector Space Projections—0
Deep Spectral Prior—0
Bayesian ensemble learning for image denoising—0
A locally statistical active contour model for SAR image segmentation can be solved by denoising algorithms—0
Deep Sparse Coding Using Optimized Linear Expansion of Thresholds—0
Bayesian ECG reconstruction using denoising diffusion generative models—0
DeepSpace: Dynamic Spatial and Source Cue Based Source Separation for Dialog Enhancement—0
Bayesian Cramér-Rao Bound Estimation with Score-Based Models—0
Almost Unsupervised Text to Speech and Automatic Speech Recognition—0
Adaptive Feature Discrimination and Denoising for Asymmetric Text Matching—0
Accelerated graph-based spectral polynomial filters—0
3D Conditional Generative Adversarial Networks to enable large-scale seismic image enhancement—0
Show:102550
← PrevPage 132 of 292Next →
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