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 47314740 of 7282 papers

TitleStatusHype
Attention-based Neural Cellular Automata0
Alternating Phase Langevin Sampling with Implicit Denoiser Priors for Phase Retrieval0
Unsupervised denoising for sparse multi-spectral computed tomography0
A new method for determining Wasserstein 1 optimal transport maps from Kantorovich potentials, with deep learning applicationsCode0
Self-supervised Physics-based Denoising for Computed Tomography0
DensePure: Understanding Diffusion Models towards Adversarial Robustness0
Denoising neural networks for magnetic resonance spectroscopy0
DiffusER: Discrete Diffusion via Edit-based Reconstruction0
LBF:Learnable Bilateral Filter For Point Cloud Denoising0
Deep network series for large-scale high-dynamic range imaging0
Show:102550
← PrevPage 474 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