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 43114320 of 7282 papers

TitleStatusHype
Diffusion-Stego: Training-free Diffusion Generative Steganography via Message Projection0
Infrared Image Deturbulence Restoration Using Degradation Parameter-Assisted Wide & Deep LearningCode0
Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold RobustnessCode0
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality ReductionCode0
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular DynamicsCode0
On the Noise Sensitivity of the Randomized SVDCode0
A Diffusion Model for Event Skeleton GenerationCode0
Error Bounds for Flow Matching Methods0
Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers0
Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent0
Show:102550
← PrevPage 432 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