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 19511960 of 7282 papers

TitleStatusHype
Learning to compress and search visual data in large-scale systemsCode0
Learning to Decouple and Generate Seismic Random Noise via Invertible Neural NetworkCode0
DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds DefenseCode0
Learning to Denoise Distantly-Labeled Data for Entity TypingCode0
Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion ModelsCode0
Defending Observation Attacks in Deep Reinforcement Learning via Detection and DenoisingCode0
Despeckling Sentinel-1 GRD images by deep learning and application to narrow river segmentationCode0
BrainCodec: Neural fMRI codec for the decoding of cognitive brain statesCode0
DestripeCycleGAN: Stripe Simulation CycleGAN for Unsupervised Infrared Image DestripingCode0
Learning the optimal Tikhonov regularizer for 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