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 1901–1925 of 7282 papers

TitleStatusHype
Immiscible Diffusion: Accelerating Diffusion Training with Noise AssignmentCode2
Crossfusor: A Cross-Attention Transformer Enhanced Conditional Diffusion Model for Car-Following Trajectory Prediction—0
Diffusion Models in Low-Level Vision: A SurveyCode4
Consistency^2: Consistent and Fast 3D Painting with Latent Consistency ModelsCode1
Latent Denoising Diffusion GAN: Faster sampling, Higher image qualityCode1
A Dictionary Based Approach for Removing Out-of-Focus BlurCode0
Noise reduction in ISAR imaging of UAVs using weighted atomic norm minimization and 2D-ADMM algorithm—0
Improving Probabilistic Diffusion Models With Optimal Covariance Matching—0
An Analysis on Quantizing Diffusion Transformers—0
Fast Unsupervised Tensor Restoration via Low-rank Deconvolution—0
Beyond the Visible: Jointly Attending to Spectral and Spatial Dimensions with HSI-Diffusion for the FINCH SpacecraftCode0
Full-reference Point Cloud Quality Assessment Using Spectral Graph Wavelets—0
Make It Count: Text-to-Image Generation with an Accurate Number of ObjectsCode2
RSEND: Retinex-based Squeeze and Excitation Network with Dark Region Detection for Efficient Low Light Image Enhancement—0
Crafting Parts for Expressive Object Composition—0
Unsupervised Monocular Depth Estimation Based on Hierarchical Feature-Guided Diffusion—0
Language-driven Grasp Detection—0
Diffusion Gaussian Mixture Audio Denoise—0
DenoiseRep: Denoising Model for Representation LearningCode1
Hybrid Spatial-spectral Neural Network for Hyperspectral Image DenoisingCode0
A Label-Free and Non-Monotonic Metric for Evaluating Denoising in Event Cameras—0
Preserving Identity with Variational Score for General-purpose 3D Editing—0
COVE: Unleashing the Diffusion Feature Correspondence for Consistent Video EditingCode1
FacEnhance: Facial Expression Enhancing with Recurrent DDPMs—0
Graph Bottlenecked Social RecommendationCode1
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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