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 4176–4200 of 7282 papers

TitleStatusHype
GeoGCN: Geometric Dual-domain Graph Convolution Network for Point Cloud Denoising—0
SG-VAD: Stochastic Gates Based Speech Activity DetectionCode1
Deep network series for large-scale high-dynamic range imaging—0
LBF:Learnable Bilateral Filter For Point Cloud Denoising—0
MagicMix: Semantic Mixing with Diffusion ModelsCode1
Diffiner: A Versatile Diffusion-based Generative Refiner for Speech EnhancementCode1
Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation—0
Generalized Laplacian Regularized Framelet Graph Neural NetworksCode0
ERNIE-ViLG 2.0: Improving Text-to-Image Diffusion Model with Knowledge-Enhanced Mixture-of-Denoising-ExpertsCode0
Topological Slepians: Maximally Localized Representations of Signals over Simplicial ComplexesCode0
Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back—0
Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence—0
Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detectionCode1
Optimization for Amortized Inverse Problems—0
Preparing fMRI Data for Statistical Analysis—0
What cleaves? Is proteasomal cleavage prediction reaching a ceiling?—0
Removing Radio Frequency Interference from Auroral Kilometric Radiation with Stacked AutoencodersCode0
ECG Artifact Removal from Single-Channel Surface EMG Using Fully Convolutional NetworksCode0
HKF: Hierarchical Kalman Filtering with Online Learned Evolution Priors for Adaptive ECG DenoisingCode0
MM-Align: Learning Optimal Transport-based Alignment Dynamics for Fast and Accurate Inference on Missing Modality SequencesCode1
Deep Equilibrium Approaches to Diffusion ModelsCode1
Diffusion Motion: Generate Text-Guided 3D Human Motion by Diffusion Model—0
Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models—0
Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological ReportCode1
Reversed Image Signal Processing and RAW Reconstruction. AIM 2022 Challenge Report—0
Show:102550
← PrevPage 168 of 292Next →
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