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 15011510 of 7282 papers

TitleStatusHype
DCT2net: an interpretable shallow CNN for image denoisingCode1
Deep Image PriorCode1
Certified Robustness for Large Language Models with Self-DenoisingCode1
Learning Degradation Representations for Image DeblurringCode1
Learning low-rank latent mesoscale structures in networksCode1
(Certified!!) Adversarial Robustness for Free!Code1
3DInvNet: A Deep Learning-Based 3D Ground-Penetrating Radar Data InversionCode1
Learning an Adaptive Model for Extreme Low-light Raw Image ProcessingCode1
Fractional Denoising for 3D Molecular Pre-trainingCode1
CERL: A Unified Optimization Framework for Light Enhancement with Realistic NoiseCode1
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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