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

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Showing 6751–6775 of 7282 papers

TitleStatusHype
Predictive Low Rank Matrix Learning under Partial Observations: Mixed-Projection ADMMCode0
Heteroskedastic PCA: Algorithm, Optimality, and ApplicationsCode0
H-FND: Hierarchical False-Negative Denoising for Distant Supervision Relation ExtractionCode0
Attention in a family of Boltzmann machines emerging from modern Hopfield networksCode0
Attention Mechanism Enhanced Kernel Prediction Networks for Denoising of Burst ImagesCode0
Hiding Images in Diffusion Models by Editing Learned Score FunctionsCode0
RGB-D-Fusion: Image Conditioned Depth Diffusion of Humanoid SubjectsCode0
HKF: Hierarchical Kalman Filtering with Online Learned Evolution Priors for Adaptive ECG DenoisingCode0
Boundary-Denoising for Video Activity LocalizationCode0
Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based RecommendationCode0
Noise Level Adaptive Diffusion Model for Robust Reconstruction of Accelerated MRICode0
Attention Based Real Image RestorationCode0
Structured Generations: Using Hierarchical Clusters to guide Diffusion ModelsCode0
Noisemaker 3D: Comprehensive Framework for Mesh Noise GenerationCode0
Airfoil Diffusion: Denoising Diffusion Model For Conditional Airfoil GenerationCode0
Hierarchical Relational Networks for Group Activity Recognition and RetrievalCode0
Separating the EoR Signal with a Convolutional Denoising Autoencoder: A Deep-learning-based MethodCode0
Attenuation of Seismic Random Noise With Unknown Distribution: A Gaussianization FrameworkCode0
Linear-Time Algorithm in Bayesian Image Denoising based on Gaussian Markov Random FieldCode0
Whitened Score Diffusion: A Structured Prior for Imaging Inverse ProblemsCode0
Linking Sketch Patches by Learning Synonymous Proximity for Graphic Sketch RepresentationCode0
High-dimensional Assisted Generative Model for Color Image RestorationCode0
LINN: Lifting Inspired Invertible Neural Network for Image DenoisingCode0
Higher fidelity perceptual image and video compression with a latent conditioned residual denoising diffusion modelCode0
Aircraft engines Remaining Useful Life prediction with an adaptive denoising online sequential Extreme Learning MachineCode0
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified