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 751–775 of 7282 papers

TitleStatusHype
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
Far3D: Expanding the Horizon for Surround-view 3D Object DetectionCode1
Deep Energy Estimator NetworksCode1
Deep Equilibrium Approaches to Diffusion ModelsCode1
EdiBERT, a generative model for image editingCode1
A Simple and Robust Correlation Filtering Method for Text-based Person SearchCode1
A tutorial on generalized eigendecomposition for denoising, contrast enhancement, and dimension reduction in multichannel electrophysiologyCode1
FastHyMix: Fast and Parameter-free Hyperspectral Image Mixed Noise RemovalCode1
EDformer: Transformer-Based Event Denoising Across Varied Noise LevelsCode1
Deep Image PriorCode1
Echo from noise: synthetic ultrasound image generation using diffusion models for real image segmentationCode1
A Two-Stage U-Net for High-Fidelity Denoising of Historical RecordingsCode1
2D medical image synthesis using transformer-based denoising diffusion probabilistic modelCode1
Deep learning architectural designs for super-resolution of noisy imagesCode1
AIM 2020 Challenge on Learned Image Signal Processing PipelineCode1
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian NoiseCode1
EC-Conf: An Ultra-fast Diffusion Model for Molecular Conformation Generation with Equivariant ConsistencyCode1
Convolutional Proximal Neural Networks and Plug-and-Play AlgorithmsCode1
Action-Conditioned 3D Human Motion Synthesis with Transformer VAECode1
CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-ThoughtCode1
EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT DenoisingCode1
Convergence Guarantees for Non-Convex Optimisation with Cauchy-Based PenaltiesCode1
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative ModelingCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Controlling Latent Diffusion Using Latent CLIPCode1
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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