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 476–500 of 7282 papers

TitleStatusHype
Interpretable Deep Learning Paradigm for Airborne Transient Electromagnetic Inversion—0
Score-Based Turbo Message Passing for Plug-and-Play Compressive Image Recovery—0
DREMnet: An Interpretable Denoising Framework for Semi-Airborne Transient Electromagnetic Signal—0
Spatial Transport Optimization by Repositioning Attention Map for Training-Free Text-to-Image Synthesis—0
Patronus: Bringing Transparency to Diffusion Models with PrototypesCode0
GCRayDiffusion: Pose-Free Surface Reconstruction via Geometric Consistent Ray Diffusion—0
RELD: Regularization by Latent Diffusion Models for Image Restoration—0
DeCompress: Denoising via Neural Compression—0
AGILE: A Diffusion-Based Attention-Guided Image and Label Translation for Efficient Cross-Domain Plant Trait IdentificationCode0
HORT: Monocular Hand-held Objects Reconstruction with Transformers—0
Diffusion Image Prior—0
Unsupervised Real-World Denoising: Sparsity is All You Need—0
Critical Iterative Denoising: A Discrete Generative Model Applied to Graphs—0
HybridoNet-Adapt: A Domain-Adapted Framework for Accurate Lithium-Ion Battery RUL Prediction—0
Optimal Stepsize for Diffusion SamplingCode3
DynamiCtrl: Rethinking the Basic Structure and the Role of Text for High-quality Human Image AnimationCode2
Implicit neural representations for end-to-end PET reconstruction—0
MAR-3D: Progressive Masked Auto-regressor for High-Resolution 3D Generation—0
Free4D: Tuning-free 4D Scene Generation with Spatial-Temporal ConsistencyCode3
ITA-MDT: Image-Timestep-Adaptive Masked Diffusion Transformer Framework for Image-Based Virtual Try-On—0
Traversing Distortion-Perception Tradeoff using a Single Score-Based Generative Model—0
Riemannian Optimization on Relaxed Indicator Matrix ManifoldCode2
Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image RestorationCode1
Exploring Robustness of Cortical Morphometry in the presence of white matter lesions, using Diffusion Models for Lesion Filling—0
Diffusion Counterfactuals for Image RegressorsCode0
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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