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 2601–2650 of 7282 papers

TitleStatusHype
Guided Image Synthesis via Initial Image Editing in Diffusion ModelCode0
Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal frameworkCode0
Dirty Pixels: Towards End-to-End Image Processing and PerceptionCode0
CoDe: Blockwise Control for Denoising Diffusion ModelsCode0
Guided and Variance-Corrected Fusion with One-shot Style Alignment for Large-Content Image GenerationCode0
HandDAGT: A Denoising Adaptive Graph Transformer for 3D Hand Pose EstimationCode0
CocoNet: A deep neural network for mapping pixel coordinates to color valuesCode0
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-ConsistencyCode0
Grids Often Outperform Implicit Neural RepresentationsCode0
Magnetogram-to-Magnetogram: Generative Forecasting of Solar EvolutionCode0
An optimized pipeline for functional connectivity analysis in the rat brainCode0
Enhanced countering adversarial attacks via input denoising and feature restoringCode0
Graph topology inference benchmarks for machine learningCode0
A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood FiltersCode0
Ground Truth Free Denoising by Optimal TransportCode0
Graph Adversarial Diffusion ConvolutionCode0
Graph Denoising with Framelet RegularizerCode0
Going beyond Compositions, DDPMs Can Produce Zero-Shot InterpolationsCode0
CNN-Based Real-Time Parameter Tuning for Optimizing Denoising Filter PerformanceCode0
Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise DetectionCode0
Global Counterfactual DirectionsCode0
A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentationCode0
Global Point Cloud Registration Network for Large TransformationsCode0
Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamicsCode0
GeoGuide: Geometric guidance of diffusion modelsCode0
GeomCLIP: Contrastive Geometry-Text Pre-training for MoleculesCode0
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational PosteriorsCode0
Cloud K-SVD for Image DenoisingCode0
GenPlan: Generative Sequence Models as Adaptive PlannersCode0
Cloud Dictionary: Sparse Coding and Modeling for Point CloudsCode0
Geometric-Facilitated Denoising Diffusion Model for 3D Molecule GenerationCode0
DiffusionTrack: Point Set Diffusion Model for Visual Object TrackingCode0
Generative Simulations of The Solar Corona Evolution With Denoising Diffusion : Proof of ConceptCode0
Generative Plug and Play: Posterior Sampling for Inverse ProblemsCode0
Generative Models Improve Radiomics Reproducibility in Low Dose CTs: A Simulation StudyCode0
Graph Signal Recovery Using Restricted Boltzmann MachinesCode0
Generative Flows as a General Purpose Solution for Inverse ProblemsCode0
Enhancing Image Resolution of Solar Magnetograms: A Latent Diffusion Model ApproachCode0
CLMB: deep contrastive learning for robust metagenomic binningCode0
Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample FilteringCode0
Generative Modeling of Microweather Wind Velocities for Urban Air MobilityCode0
Generating Training Data for Denoising Real RGB Images via Camera Pipeline SimulationCode0
Generative Modeling of Seismic Data using Diffusion Models and its Application to Multi-Purpose Seismic Inverse ProblemsCode0
Generating observation guided ensembles for data assimilation with denoising diffusion probabilistic modelCode0
Robust Simultaneous Multislice MRI Reconstruction Using Deep Generative PriorsCode0
Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-DecodingCode0
Generating Classification Weights with GNN Denoising Autoencoders for Few-Shot LearningCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and EnhancementCode0
Anomaly Detection with Robust Deep AutoencodersCode0
Generalized Robust Fundus Photography-based Vision Loss Estimation for High MyopiaCode0
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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