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 7051–7100 of 7282 papers

TitleStatusHype
Contrastive Principal Component AnalysisCode0
Imaging at the quantum limit with convolutional neural networksCode0
Exploring validation metrics for offline model-based optimisation with diffusion modelsCode0
Enhancing Conditional Image Generation with Explainable Latent Space ManipulationCode0
Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomyCode0
MCRAGE: Synthetic Healthcare Data for FairnessCode0
Contrastive Sequential-Diffusion Learning: Non-linear and Multi-Scene Instructional Video SynthesisCode0
Robust multi-coil MRI reconstruction via self-supervised denoisingCode0
Enhancing Diffusion-Based Image Synthesis with Robust Classifier GuidanceCode0
An optimized pipeline for functional connectivity analysis in the rat brainCode0
Audio Source Separation Using Variational Autoencoders and Weak Class SupervisionCode0
QNCD: Quantization Noise Correction for Diffusion ModelsCode0
rVAD: An Unsupervised Segment-Based Robust Voice Activity Detection MethodCode0
Tuning-free Plug-and-Play Hyperspectral Image Deconvolution with Deep PriorsCode0
Implicit 3D Orientation Learning for 6D Object Detection from RGB ImagesCode0
QS-ADN: Quasi-Supervised Artifact Disentanglement Network for Low-Dose CT Image Denoising by Local Similarity Among Unpaired DataCode0
Enhancing Image Resolution of Solar Magnetograms: A Latent Diffusion Model ApproachCode0
Deep Learning strategies for ProtoDUNE raw data denoisingCode0
Implicit Image-to-Image Schrodinger Bridge for Image RestorationCode0
Enhancing LLM Robustness to Perturbed Instructions: An Empirical StudyCode0
Deep learning for denoisingCode0
Quadratic Autoencoder (Q-AE) for Low-dose CT DenoisingCode0
An Efficient End-to-End Approach to Noise Invariant Speech Features via Multi-Task LearningCode0
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular DynamicsCode0
Fréchet Denoised Distance: Enhancing Plausibility Evaluation for Generated Designs with Denoising AutoencoderCode0
The Devil's Advocate: Shattering the Illusion of Unexploitable Data using Diffusion ModelsCode0
A note on the evaluation of generative modelsCode0
ImPoster: Text and Frequency Guidance for Subject Driven Action Personalization using Diffusion ModelsCode0
Deep Sparse and Low-Rank Prior for Hyperspectral Image DenoisingCode0
Tuning-Free Visual Customization via View Iterative Self-Attention ControlCode0
Quantization-Based Regularization for AutoencodersCode0
Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?Code0
Improved Diffusion-based Generative Model with Better Adversarial RobustnessCode0
Medical image denoising using convolutional denoising autoencodersCode0
Can denoising diffusion probabilistic models generate realistic astrophysical fields?Code0
Ensembling Diffusion Models via Adaptive Feature AggregationCode0
A Weighted Difference of Anisotropic and Isotropic Total Variation for Relaxed Mumford-Shah Color and Multiphase Image SegmentationCode0
Quantum Annealing for Robust Principal Component AnalysisCode0
SU-YOLO: Spiking Neural Network for Efficient Underwater Object DetectionCode0
Improved Out-of-Scope Intent Classification with Dual Encoding and Threshold-based Re-ClassificationCode0
Decoding Phone Pairs from MEG Signals Across Speech ModalitiesCode0
Megapixel Image Generation with Step-Unrolled Denoising AutoencodersCode0
Equivariant Blurring Diffusion for Hierarchical Molecular Conformer GenerationCode0
Decoding the shift-invariant data: applications for band-excitation scanning probe microscopyCode0
Quantum Diffusion Model for Quark and Gluon Jet GenerationCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and EnhancementCode0
A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentationCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Frame Interpolation and EnhancementCode0
DARK: Denoising, Amplification, Restoration KitCode0
The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture ModelCode0
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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