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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3726–3750 of 7282 papers

TitleStatusHype
Extrapolating Multilingual Understanding Models as Multilingual Generators—0
Extreme Low-Light Environment-Driven Image Denoising Over Permanently Shadowed Lunar Regions With a Physical Noise Model—0
Eye-Movement behavior identification for AD diagnosis—0
A General Unified Graph Neural Network Framework Against Adversarial Attacks—0
FabricDiffusion: High-Fidelity Texture Transfer for 3D Garments Generation from In-The-Wild Clothing Images—0
FacEnhance: Facial Expression Enhancing with Recurrent DDPMs—0
FaceShield: Defending Facial Image against Deepfake Threats—0
Factor Adjusted Spectral Clustering for Mixture Models—0
Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation—0
Factorized Diffusion: Perceptual Illusions by Noise Decomposition—0
Fair Primal Dual Splitting Method for Image Inverse Problems—0
FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation—0
Synergy Between Semantic Segmentation and Image Denoising via Alternate Boosting—0
FaR: Enhancing Multi-Concept Text-to-Image Diffusion via Concept Fusion and Localized Refinement—0
Far-Field Speaker Recognition Benchmark Derived From The DiPCo Corpus—0
Fast 3D Point Cloud Denoising via Bipartite Graph Approximation & Total Variation—0
Fast, Accurate Manifold Denoising by Tunneling Riemannian Optimization—0
Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion—0
Fast and Flexible Image Blind Denoising via Competition of Experts—0
Fast and High-Quality Image Denoising via Malleable Convolutions—0
Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution—0
Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent—0
Fast and Provable ADMM for Learning with Generative Priors—0
Virtual SAR: A Synthetic Dataset for Deep Learning based Speckle Noise Reduction Algorithms—0
Fast and Robust Visuomotor Riemannian Flow Matching Policy—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