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 851–875 of 7282 papers

TitleStatusHype
D^2-DPM: Dual Denoising for Quantized Diffusion Probabilistic ModelsCode1
Generative AI Enabled Robust Sensor Placement in Cyber-Physical Power Systems: A Graph Diffusion Approach—0
Wavelet Integrated Convolutional Neural Network for ECG Signal Denoising—0
ODPG: Outfitting Diffusion with Pose Guided Condition—0
Comparison of Autoencoders for tokenization of ASL datasets—0
Quantum Annealing for Robust Principal Component AnalysisCode0
LLVD: LSTM-based Explicit Motion Modeling in Latent Space for Blind Video Denoising—0
Towards Balanced Continual Multi-Modal Learning in Human Pose Estimation—0
Targeted Adversarial Denoising Autoencoders (TADA) for Neural Time Series Filtration—0
D3RM: A Discrete Denoising Diffusion Refinement Model for Piano TranscriptionCode1
Tuning-Free Long Video Generation via Global-Local Collaborative Diffusion—0
Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration—0
Geophysical inverse problems with measurement-guided diffusion models—0
MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image RestorationCode2
Exploring Molecule Generation Using Latent Space Graph DiffusionCode0
FgC2F-UDiff: Frequency-guided and Coarse-to-fine Unified Diffusion Model for Multi-modality Missing MRI SynthesisCode1
Exploring Optimal Latent Trajetory for Zero-shot Image Editing—0
A Self-supervised Diffusion Bridge for MRI Reconstruction—0
Noise-Robust Target-Speaker Voice Activity Detection Through Self-Supervised Pretraining—0
InpDiffusion: Image Inpainting Localization via Conditional Diffusion Models—0
DDRM-PR: Fourier Phase Retrieval using Denoising Diffusion Restoration Models—0
Two-Dimensional Unknown View Tomography from Unknown Angle Distributions—0
DarkFarseer: Inductive Spatio-temporal Kriging via Hidden Style Enhancement and Sparsity-Noise Mitigation—0
Brick-Diffusion: Generating Long Videos with Brick-to-Wall Denoising—0
MedSegDiffNCA: Diffusion Models With Neural Cellular Automata for Skin Lesion Segmentation—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