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 20312040 of 7282 papers

TitleStatusHype
Deep Neural Networks Motivated by Partial Differential EquationsCode0
Learning Dynamics of Linear Denoising AutoencodersCode0
Learning Deep Representations Using Convolutional Auto-encoders with Symmetric Skip ConnectionsCode0
Learning in Deep Factor Graphs with Gaussian Belief PropagationCode0
Learning normalized image densities via dual score matchingCode0
Learning the optimal Tikhonov regularizer for inverse problemsCode0
Learned Convolutional Sparse CodingCode0
Learned D-AMP: Principled Neural Network based Compressive Image RecoveryCode0
Layered Rendering Diffusion Model for Controllable Zero-Shot Image SynthesisCode0
Back-Projection based Fidelity Term for Ill-Posed Linear Inverse ProblemsCode0
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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