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 16011625 of 7282 papers

TitleStatusHype
A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding OptimizationCode1
How Framelets Enhance Graph Neural NetworksCode1
Homotopic Gradients of Generative Density Priors for MR Image ReconstructionCode1
Selective Residual M-Net for Real Image DenoisingCode1
Low-dose CT Denoising with Language-engaged Dual-space AlignmentCode1
Deep Reparametrization of Multi-Frame Super-Resolution and DenoisingCode1
How to Backdoor Diffusion Models?Code1
Deep Image PriorCode1
Deep Recurrent Neural Networks for ECG Signal DenoisingCode1
How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk ControlCode1
Exploring the Loss Landscape in Neural Architecture SearchCode1
Deep Random Projector: Accelerated Deep Image PriorCode1
Localizing Object-level Shape Variations with Text-to-Image Diffusion ModelsCode1
Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual LossCode1
M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI researchCode1
Adaptive Differential Denoising for Respiratory Sounds ClassificationCode1
HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising PackageCode1
Deep learning architectural designs for super-resolution of noisy imagesCode1
A Light and Tuning-free Method for Simulating Camera Motion in Video GenerationCode1
Hyperspectral and Multispectral Image Fusion Using the Conditional Denoising Diffusion Probabilistic ModelCode1
Listening to Sounds of Silence for Speech DenoisingCode1
The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven InitializationCode1
3D^2-Actor: Learning Pose-Conditioned 3D-Aware Denoiser for Realistic Gaussian Avatar ModelingCode1
Hyperspectral Image Denoising Using SURE-Based Unsupervised Convolutional Neural NetworksCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video 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