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 1551–1600 of 7282 papers

TitleStatusHype
Learning to Drop: Robust Graph Neural Network via Topological DenoisingCode1
Noise Conscious Training of Non Local Neural Network powered by Self Attentive Spectral Normalized Markovian Patch GAN for Low Dose CT DenoisingCode1
AIM 2020 Challenge on Learned Image Signal Processing PipelineCode1
Denoising Relation Extraction from Document-level Distant SupervisionCode1
Suppression of Correlated Noise with Similarity-based Unsupervised Deep LearningCode1
Convolutional Proximal Neural Networks and Plug-and-Play AlgorithmsCode1
BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image RestorationCode1
Solving Inverse Problems with Hybrid Deep Image Priors: the challenge of preventing overfittingCode1
Patch2Self: Denoising Diffusion MRI with Self-Supervised LearningCode1
EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT DenoisingCode1
Deep Denoising For Scientific Discovery: A Case Study In Electron MicroscopyCode1
Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image RestorationCode1
Progressive Training of Multi-level Wavelet Residual Networks for Image DenoisingCode1
Listening to Sounds of Silence for Speech DenoisingCode1
Noise2Same: Optimizing A Self-Supervised Bound for Image DenoisingCode1
One Model to Reconstruct Them All: A Novel Way to Use the Stochastic Noise in StyleGANCode1
Practical Deep Raw Image Denoising on Mobile DevicesCode1
Graph Information Bottleneck for Subgraph RecognitionCode1
Denoising Multi-Source Weak Supervision for Neural Text ClassificationCode1
G-SimCLR: Self-Supervised Contrastive Learning with Guided Projection via Pseudo LabellingCode1
High-throughput molecular imaging via deep learning enabled Raman spectroscopyCode1
G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo LabellingCode1
EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoisingCode1
Joint ptycho-tomography with deep generative priorsCode1
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from DataCode1
Unit Test Case Generation with Transformers and Focal ContextCode1
Adversarial score matching and improved sampling for image generationCode1
Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data HidingCode1
Are Deep Neural Architectures Losing Information? Invertibility Is IndispensableCode1
Deep Residual Learning for Channel Estimation in Intelligent Reflecting Surface-Assisted Multi-User CommunicationsCode1
Open-set Adversarial DefenseCode1
Unpaired Learning of Deep Image DenoisingCode1
FLIP: A Difference Evaluator for Alternating ImagesCode1
Block-wise Minimization-Majorization algorithm for Huber's criterion: sparse learning and applicationsCode1
Deep Variational Network Toward Blind Image RestorationCode1
Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image PriorCode1
Improving Blind Spot Denoising for MicroscopyCode1
Homotopic Gradients of Generative Density Priors for MR Image ReconstructionCode1
Distantly Supervised Relation Extraction in Federated SettingsCode1
Low-Light Maritime Image Enhancement with Regularized Illumination Optimization and Deep Noise SuppressionCode1
Enhancing Robustness Against Adversarial Examples in Network Intrusion Detection SystemsCode1
Spatial Hierarchy Aware Residual Pyramid Network for Time-of-Flight Depth DenoisingCode1
Joint Low Dose CT Denoising And Kidney SegmentationCode1
NormalGAN: Learning Detailed 3D Human from a Single RGB-D ImageCode1
Solving Linear Inverse Problems Using the Prior Implicit in a DenoiserCode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
Hyperspectral Image Denoising Using SURE-Based Unsupervised Convolutional Neural NetworksCode1
Event Enhanced High-Quality Image RecoveryCode1
Transformation Consistency Regularization- A Semi-Supervised Paradigm for Image-to-Image TranslationCode1
Unsupervised 3D Human Pose Representation with Viewpoint and Pose DisentanglementCode1
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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