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 3151–3200 of 7282 papers

TitleStatusHype
A Self-Supervised Algorithm for Denoising Photoplethysmography Signals for Heart Rate Estimation from Wearables—0
Generative Joint Source-Channel Coding for Semantic Image Transmission—0
Error analysis for denoising smooth modulo signals on a graph—0
Generative Lines Matching Models—0
Generative method for aerodynamic optimization based on classifier-free guided denoising diffusion probabilistic model—0
Generative Model for Heterogeneous Inference—0
On Convex Duality in Linear Inverse Problems—0
Automated Channel Pruning with Learned Importance—0
AE-RED: A Hyperspectral Unmixing Framework Powered by Deep Autoencoder and Regularization by Denoising—0
A Cross Validation Framework for Signal Denoising with Applications to Trend Filtering, Dyadic CART and Beyond—0
Deep Denoising Prior-Based Spectral Estimation for Phaseless Synthetic Aperture Radar—0
ERNet Family: Hardware-Oriented CNN Models for Computational Imaging Using Block-Based Inference—0
"Generative Models for Financial Time Series Data: Enhancing Signal-to-Noise Ratio and Addressing Data Scarcity in A-Share Market—0
Generative Models for Low-Dimensional Video Representation and Compressive Sensing—0
Deep Denoising: Rate-Optimal Recovery of Structured Signals with a Deep Prior—0
Generative Models Improve Radiomics Performance in Different Tasks and Different Datasets: An Experimental Study—0
ERD: Exponential Retinex decomposition based on weak space and hybrid nonconvex regularization and its denoising application—0
Depth Completion Using a View-constrained Deep Prior—0
Generative Precipitation Downscaling using Score-based Diffusion with Wasserstein Regularization—0
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks with Soft-Thresholding—0
ERA-Solver: Error-Robust Adams Solver for Fast Sampling of Diffusion Probabilistic Models—0
EraseNet: A Recurrent Residual Network for Supervised Document Cleaning—0
Convex Denoising using Non-Convex Tight Frame Regularization—0
Generative Recommendation with Continuous-Token Diffusion—0
Deep Encoder-Decoder Neural Network for Fingerprint Image Denoising and Inpainting—0
Generative Speech Foundation Model Pretraining for High-Quality Speech Extraction and Restoration—0
Generative thermodynamic computing—0
A Self-Refinement Strategy for Noise Reduction in Grammatical Error Correction—0
HLRTF: Hierarchical Low-Rank Tensor Factorization for Inverse Problems in Multi-Dimensional Imaging—0
GenesisTex: Adapting Image Denoising Diffusion to Texture Space—0
HOIAnimator: Generating Text-prompt Human-object Animations using Novel Perceptive Diffusion Models—0
Converting Anyone's Voice: End-to-End Expressive Voice Conversion with a Conditional Diffusion Model—0
Application of Spherical Convolutional Neural Networks to Image Reconstruction and Denoising in Nuclear Medicine—0
An Equivariant Pretrained Transformer for Unified 3D Molecular Representation Learning—0
Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models—0
GenzIQA: Generalized Image Quality Assessment using Prompt-Guided Latent Diffusion Models—0
A Second Order Cumulant Spectrum Test That a Stochastic Process is Strictly Stationary and a Step Toward a Test for Graph Signal Strict Stationarity—0
Equivariant plug-and-play image reconstruction—0
Geodesic Gramian Denoising Applied to the Images Contaminated With Noise Sampled From Diverse Probability Distributions—0
GeoDirDock: Guiding Docking Along Geodesic Paths—0
Equivariant Denoisers for Image Restoration—0
Convergent regularization in inverse problems and linear plug-and-play denoisers—0
Deep Gaussian Conditional Random Field Network: A Model-based Deep Network for Discriminative Denoising—0
Improved Techniques for Adversarial Discriminative Domain Adaptation—0
Geometric and Learning-based Mesh Denoising: A Comprehensive Survey—0
Geometric Constraints in Probabilistic Manifolds: A Bridge from Molecular Dynamics to Structured Diffusion Processes—0
Deep Generative Models for 3D Medical Image Synthesis—0
Geometric Machine Learning on EEG Signals—0
ASD-Diffusion: Anomalous Sound Detection with Diffusion Models—0
EP-CFG: Energy-Preserving Classifier-Free Guidance—0
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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