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 4126–4150 of 7282 papers

TitleStatusHype
Autonomous Point Cloud Segmentation for Power Lines Inspection in Smart Grid—0
DiffSED: Sound Event Detection with Denoising Diffusion—0
PGT-Net: Progressive Guided Multi-task Neural Network for Small-area Wet Fingerprint Denoising and Recognition—0
Self-supervised Noise2noise Method Utilizing Corrupted Images with a Modular Network for LDCT DenoisingCode0
Generating observation guided ensembles for data assimilation with denoising diffusion probabilistic modelCode0
Accelerating Diffusion-based Combinatorial Optimization Solvers by Progressive Distillation—0
Illumination and Shadows in Head Rotation: experiments with Denoising Diffusion Models—0
TriDo-Former: A Triple-Domain Transformer for Direct PET Reconstruction from Low-Dose Sinograms—0
On Error Propagation of Diffusion Models—0
Optimizing a Transformer-based network for a deep learning seismic processing workflow—0
Deep Learning Architecture for Motor Imaged Words—0
3D Scene Diffusion Guidance using Scene Graphs—0
Evaluation of a Low-Cost Single-Lead ECG Module for Vascular Ageing Prediction and Studying Smoking-induced Changes in ECG—0
Target Speech Extraction with Conditional Diffusion Model—0
Assessing Adversarial Replay and Deep Learning-Driven Attacks on Specific Emitter Identification-based Security Approaches—0
Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization—0
Recurrent Self-Supervised Video Denoising with Denser Receptive FieldCode0
All-in-one Multi-degradation Image Restoration Network via Hierarchical Degradation Representation—0
Recurrent Spike-based Image Restoration under General IlluminationCode0
Unfolded proximal neural networks for robust image Gaussian denoising—0
Sketch and Text Guided Diffusion Model for Colored Point Cloud Generation—0
Non-line-of-sight reconstruction via structure sparsity regularization—0
Transformer-Based Denoising of Mechanical Vibration Signals—0
SDDM: Score-Decomposed Diffusion Models on Manifolds for Unpaired Image-to-Image Translation—0
Rethinking Class Activation Maps for Segmentation: Revealing Semantic Information in Shallow Layers by Reducing Noise—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