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 14261450 of 7282 papers

TitleStatusHype
Noise2Fast: Fast Self-Supervised Single Image Blind DenoisingCode1
Deep Reparametrization of Multi-Frame Super-Resolution and DenoisingCode1
Thermal Image Processing via Physics-Inspired Deep NetworksCode1
spectrai: A deep learning framework for spectral dataCode1
ILVR: Conditioning Method for Denoising Diffusion Probabilistic ModelsCode1
Optimal Transport for Unsupervised Denoising LearningCode1
Physics-based Noise Modeling for Extreme Low-light PhotographyCode1
Toward Spatially Unbiased Generative ModelsCode1
CERL: A Unified Optimization Framework for Light Enhancement with Realistic NoiseCode1
DCT2net: an interpretable shallow CNN for image denoisingCode1
Score-Based Point Cloud DenoisingCode1
Wavelet Transform-assisted Adaptive Generative Modeling for ColorizationCode1
On Measuring and Controlling the Spectral Bias of the Deep Image PriorCode1
Deep Mesh Prior: Unsupervised Mesh Restoration using Graph Convolutional NetworksCode1
DAEMA: Denoising Autoencoder with Mask AttentionCode1
Uncertainty-Guided Progressive GANs for Medical Image TranslationCode1
R2RNet: Low-light Image Enhancement via Real-low to Real-normal NetworkCode1
Progressive Joint Low-light Enhancement and Noise Removal for Raw ImagesCode1
Fast Monte Carlo Rendering via Multi-Resolution SamplingCode1
Deformed2Self: Self-Supervised Denoising for Dynamic Medical ImagingCode1
Deep Convolutional Dictionary Learning for Image DenoisingCode1
Adaptive Consistency Prior Based Deep Network for Image DenoisingCode1
Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image DenoisingCode1
Effective Snapshot Compressive-Spectral Imaging via Deep Denoising and Total Variation PriorsCode1
End-to-End Learning for Joint Image Demosaicing, Denoising and Super-ResolutionCode1
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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