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 2801–2850 of 7282 papers

TitleStatusHype
DiffuseDef: Improved Robustness to Adversarial Attacks via Iterative DenoisingCode0
DiffuScene: Denoising Diffusion Models for Generative Indoor Scene SynthesisCode0
DiffuPose: Monocular 3D Human Pose Estimation via Denoising Diffusion Probabilistic ModelCode0
CAT Pruning: Cluster-Aware Token Pruning For Text-to-Image Diffusion ModelsCode0
FAP-CD: Fairness-Driven Age-Friendly Community Planning via Conditional Diffusion GenerationCode0
Foundation Models For Seismic Data Processing: An Extensive ReviewCode0
FlexControl: Computation-Aware ControlNet with Differentiable Router for Text-to-Image GenerationCode0
Accurate Segmentation of Optic Disc And Cup from Multiple Pseudo-labels by Noise-aware LearningCode0
FASPell: A Fast, Adaptable, Simple, Powerful Chinese Spell Checker Based On DAE-Decoder ParadigmCode0
An Extended Framework for Marginalized Domain AdaptationCode0
Flashlight CNN Image DenoisingCode0
Fast Algorithm for Constrained Linear Inverse ProblemsCode0
FiRe: Fixed-points of Restoration Priors for Solving Inverse ProblemsCode0
Fast and Differentiable Message Passing on Pairwise Markov Random FieldsCode0
First image then video: A two-stage network for spatiotemporal video denoisingCode0
Fingerprint Presentation Attack Detection by Channel-wise Feature DenoisingCode0
First line of defense: A robust first layer mitigates adversarial attacksCode0
A denoised Mean Teacher for domain adaptive point cloud registrationCode0
Fine-grained Contrastive Learning for Relation ExtractionCode0
Fine-grained Forecasting Models Via Gaussian Process Blurring EffectCode0
FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural NetworksCode0
DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local SmoothingCode0
Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated CasesCode0
A New Multi-Picture Architecture for Learned Video Deinterlacing and Demosaicing with Parallel Deformable Convolution and Self-Attention BlocksCode0
DiffSCI: Zero-Shot Snapshot Compressive Imaging via Iterative Spectral Diffusion ModelCode0
Few-shot point cloud reconstruction and denoising via learned Guassian splats renderings and fine-tuned diffusion featuresCode0
FFDNet: Toward a Fast and Flexible Solution for CNN based Image DenoisingCode0
FIND: Fine-tuning Initial Noise Distribution with Policy Optimization for Diffusion ModelsCode0
Few Clean Instances Help Denoising Distant SupervisionCode0
Few-shot Image Generation with Diffusion ModelsCode0
Can learning from natural image denoising be used for seismic data interpolation?Code0
FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow EstimationCode0
FEUNet: a flexible and effective U-shaped network for image denoisingCode0
Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure PredictionCode0
Finding Local Diffusion Schrödinger Bridge using Kolmogorov-Arnold NetworkCode0
Feature-Based Image Clustering and Segmentation Using WaveletsCode0
A new method for determining Wasserstein 1 optimal transport maps from Kantorovich potentials, with deep learning applicationsCode0
FDG-Diff: Frequency-Domain-Guided Diffusion Framework for Compressed Hazy Image RestorationCode0
Feature Enhancement with Deep Feature Losses for Speaker VerificationCode0
Can denoising diffusion probabilistic models generate realistic astrophysical fields?Code0
DiffPAD: Denoising Diffusion-based Adversarial Patch DecontaminationCode0
fastWDM3D: Fast and Accurate 3D Healthy Tissue InpaintingCode0
FDF: Flexible Decoupled Framework for Time Series Forecasting with Conditional Denoising and Polynomial ModelingCode0
DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech TranslationCode0
Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?Code0
DiffMotion: Speech-Driven Gesture Synthesis Using Denoising Diffusion ModelCode0
Fast Multi-grid Methods for Minimizing Curvature EnergyCode0
Fast Track to Winning Tickets: Repowering One-Shot Pruning for Graph Neural NetworksCode0
FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET DenoisingCode0
Finding Local Diffusion Schrodinger Bridge using Kolmogorov-Arnold NetworkCode0
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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