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

Showing 24512475 of 7282 papers

TitleStatusHype
IFH: a Diffusion Framework for Flexible Design of Graph Generative ModelsCode0
Composite Reward Design in PPO-Driven Adaptive FilteringCode0
IFR-Net: Iterative Feature Refinement Network for Compressed Sensing MRICode0
Concept Replacer: Replacing Sensitive Concepts in Diffusion Models via Precision LocalizationCode0
A Plug-and-Play Priors Framework for Hyperspectral UnmixingCode0
IIDM: Image-to-Image Diffusion Model for Semantic Image SynthesisCode0
Image Denoising with Graph-Convolutional Neural NetworksCode0
IBO: Inpainting-Based Occlusion to Enhance Explainable Artificial Intelligence Evaluation in HistopathologyCode0
DreamSteerer: Enhancing Source Image Conditioned Editability using Personalized Diffusion ModelsCode0
A Comprehensive Comparison of Multi-Dimensional Image Denoising MethodsCode0
Hyperspectral Mixed Noise Removal By L1-Norm-Based Subspace RepresentationCode0
Dreaming of Electrical Waves: Generative Modeling of Cardiac Excitation Waves using Diffusion ModelsCode0
Complex Signal Denoising and Interference Mitigation for Automotive Radar Using Convolutional Neural NetworksCode0
Identifying Recurring Patterns with Deep Neural Networks for Natural Image DenoisingCode0
Hyperspectral Image Denoising via Spatial-Spectral Recurrent TransformerCode0
Hyperspectral Image Denoising via Self-Modulating Convolutional Neural NetworksCode0
A Projectional Ansatz to ReconstructionCode0
Complex Image Generation SwinTransformer Network for Audio DenoisingCode0
Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural NetworkCode0
Inference-Time Diffusion Model DistillationCode0
Hyperspectral Image Denoising and Anomaly Detection Based on Low-rank and Sparse RepresentationsCode0
Hyperspectral Image Mixed Noise Removal Using Subspace Representation and Deep CNN Image PriorCode0
Identity Enhanced Residual Image DenoisingCode0
Compensation Sampling for Improved Convergence in Diffusion ModelsCode0
HyperAid: Denoising in hyperbolic spaces for tree-fitting and hierarchical clusteringCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified