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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 6151–6200 of 7282 papers

TitleStatusHype
Satellite to GroundScape - Large-scale Consistent Ground View Generation from Satellite Views—0
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation—0
Scalable AI Framework for Defect Detection in Metal Additive Manufacturing—0
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models—0
Scalable Lossless Coding of Dynamic Medical CT Data Using Motion Compensated Wavelet Lifting with Denoised Prediction and Update—0
Scalable Non-Cartesian Magnetic Resonance Imaging with R2D2—0
Scale-Agnostic Super-Resolution in MRI using Feature-Based Coordinate Networks—0
Zero-Shot Voice Conditioning for Denoising Diffusion TTS Models—0
Vector-Valued Graph Trend Filtering with Non-Convex PenaltiesCode0
BNEM: A Boltzmann Sampler Based on Bootstrapped Noised Energy MatchingCode0
U-DECN: End-to-End Underwater Object Detection ConvNet with Improved DeNoising TrainingCode0
Moiré Photo Restoration Using Multiresolution Convolutional Neural NetworksCode0
Solving Inverse Problems by Joint Posterior Maximization with Autoencoding PriorCode0
Data-Driven Score-Based Models for Generating Stable Structures with Adaptive Crystal CellsCode0
Démélange, déconvolution et débruitage conjoints d'un modèle convolutif parcimonieux avec dérive instrumentale, par pénalisation de rapports de normes ou quasi-normes lissées (PENDANTSS)Code0
Sparse Geometric Representation Through Local Shape ProbingCode0
Moment Matching Denoising Gibbs SamplingCode0
AGEM: Solving Linear Inverse Problems via Deep Priors and SamplingCode0
Dendritic error backpropagation in deep cortical microcircuitsCode0
Fast Track to Winning Tickets: Repowering One-Shot Pruning for Graph Neural NetworksCode0
A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGACode0
AGConv: Adaptive Graph Convolution on 3D Point CloudsCode0
Are deep learning models superior for missing data imputation in large surveys? Evidence from an empirical comparisonCode0
GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature Guided DDPMCode0
Invertible generative models for inverse problems: mitigating representation error and dataset biasCode0
Denoise-I2W: Mapping Images to Denoising Words for Accurate Zero-Shot Composed Image RetrievalCode0
Spectrum-Guided Adversarial Disparity LearningCode0
Invertible Kernel PCA with Random Fourier FeaturesCode0
fastWDM3D: Fast and Accurate 3D Healthy Tissue InpaintingCode0
Data-driven Thresholding in Denoising with Spectral Graph Wavelet TransformCode0
U-Finger: Multi-Scale Dilated Convolutional Network for Fingerprint Image Denoising and InpaintingCode0
Channel-aware Contrastive Conditional Diffusion for Multivariate Probabilistic Time Series ForecastingCode0
Investigating the effect of residual and highway connections in speech enhancement modelsCode0
FDF: Flexible Decoupled Framework for Time Series Forecasting with Conditional Denoising and Polynomial ModelingCode0
FDG-Diff: Frequency-Domain-Guided Diffusion Framework for Compressed Hazy Image RestorationCode0
Overcoming Dimensional Factorization Limits in Discrete Diffusion Models through Quantum Joint Distribution LearningCode0
Unrolling of Deep Graph Total Variation for Image DenoisingCode0
Multi-scale Processing of Noisy Images using Edge Preservation LossesCode0
Deep Pairwise Hashing for Cold-start RecommendationCode0
A Complementary Global and Local Knowledge Network for Ultrasound denoising with Fine-grained RefinementCode0
Denoising and Regularization via Exploiting the Structural Bias of Convolutional GeneratorsCode0
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style TransferCode0
Feature-Based Image Clustering and Segmentation Using WaveletsCode0
Convexified Convolutional Neural NetworksCode0
Denoising Architecture for Unsupervised Anomaly Detection in Time-SeriesCode0
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold SimplificationCode0
An adaptive denoising recommendation algorithm for causal separation biasCode0
Unsupervised Training of a Dynamic Context-Aware Deep Denoising Framework for Low-Dose Fluoroscopic ImagingCode0
Feature Enhancement with Deep Feature Losses for Speaker VerificationCode0
Recovering Hölder smooth functions from noisy modulo samplesCode0
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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