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 4951–4975 of 7282 papers

TitleStatusHype
Identifying Arrhythmias Based on ECG Classification Using Enhanced-PCA and Enhanced-SVM Methods—0
An Effective Fusion Method to Enhance the Robustness of CNN—0
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative ModelsCode0
A hybrid approach to seismic deblending: when physics meets self-supervision—0
E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and GenerationCode0
ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge SplittingCode0
Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models—0
Fine-grained Contrastive Learning for Relation ExtractionCode0
Thunder: Thumbnail based Fast Lightweight Image Denoising Network—0
Denoising-based image reconstruction from pixels located at non-integer positions—0
A Coupling Enhancement Algorithm for ZrO2 Ceramic Bearing Ball Surface Defect Detection Based on Cartoon-texture Decomposition Model and Multi-Scale Filtering Method—0
Multi-Agent Feedback Enabled Neural Networks for Intelligent CommunicationsCode0
AutoJoin: Efficient Adversarial Training against Gradient-Free Perturbations for Robust Maneuvering via Denoising Autoencoder and Joint LearningCode0
Reliability-based Mesh-to-Grid Image Reconstruction—0
HyperAid: Denoising in hyperbolic spaces for tree-fitting and hierarchical clusteringCode0
A Simple Yet Effective SVD-GCN for Directed GraphsCode0
Evaluation of Transfer Learning for Polish with a Text-to-Text Model—0
Exploiting Social Media Content for Self-Supervised Style TransferCode0
A Survey on Hyperspectral Image Restoration: From the View of Low-Rank Tensor Approximation—0
A Framework for CSI-Based Indoor Localization with 1D Convolutional Neural Networks—0
Variational Quantum Compressed Sensing for Joint User and Channel State Acquisition in Grant-Free Device Access Systems—0
TOCH: Spatio-Temporal Object-to-Hand Correspondence for Motion Refinement—0
Low power communication signal enhancement method of Internet of things based on nonlocal mean denoising—0
Dense residual Transformer for image denoising—0
Simple Contrastive Graph Clustering—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