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 19411950 of 7282 papers

TitleStatusHype
BORT: Back and Denoising Reconstruction for End-to-End Task-Oriented DialogCode0
Noise Adaption Network for Morse Code Image ClassificationCode0
Learning to Kindle the StarlightCode0
Learning to Generate Samples from Noise through Infusion TrainingCode0
Learning to Separate Object Sounds by Watching Unlabeled VideoCode0
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor ContractionsCode0
MambaFoley: Foley Sound Generation using Selective State-Space ModelsCode0
Learning to compress and search visual data in large-scale systemsCode0
Learning to Bound: A Generative Cramér-Rao BoundCode0
Learning to Decouple and Generate Seismic Random Noise via Invertible Neural NetworkCode0
Show:102550
← PrevPage 195 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