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 15011525 of 7282 papers

TitleStatusHype
DCT2net: an interpretable shallow CNN for image denoisingCode1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
CERL: A Unified Optimization Framework for Light Enhancement with Realistic NoiseCode1
Deep Image PriorCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video DenoisingCode1
DDIM sampling for Generative AIBIM, a faster intelligent structural design frameworkCode1
DDM^2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion ModelsCode1
LenslessPiCam: A Hardware and Software Platform for Lensless Computational Imaging with a Raspberry PiCode1
Listening to Sounds of Silence for Speech DenoisingCode1
Learning from Rules Generalizing Labeled ExemplarsCode1
Frido: Feature Pyramid Diffusion for Complex Scene Image SynthesisCode1
From Denoising to Compressed SensingCode1
From Denoising Diffusions to Denoising Markov ModelsCode1
A tutorial on generalized eigendecomposition for denoising, contrast enhancement, and dimension reduction in multichannel electrophysiologyCode1
Quantum circuit synthesis with diffusion modelsCode1
From Rank Estimation to Rank Approximation: Rank Residual Constraint for Image RestorationCode1
Deep Equilibrium Approaches to Diffusion ModelsCode1
DDT: Dual-branch Deformable Transformer for Image DenoisingCode1
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-ExpertsCode1
Fully Convolutional Pixel Adaptive Image DenoiserCode1
Radio-astronomical Image Reconstruction with Conditional Denoising Diffusion ModelCode1
Learning Graph-Convolutional Representations for Point Cloud DenoisingCode1
Random Sub-Samples Generation for Self-Supervised Real Image DenoisingCode1
CDLNet: Robust and Interpretable Denoising Through Deep Convolutional Dictionary LearningCode1
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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