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 1126–1150 of 7282 papers

TitleStatusHype
P+: Extended Textual Conditioning in Text-to-Image GenerationCode1
Stochastic Segmentation with Conditional Categorical Diffusion ModelsCode1
Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class LabelsCode1
Robust Preference-Guided Denoising for Graph based Social RecommendationCode1
DR2: Diffusion-based Robust Degradation Remover for Blind Face RestorationCode1
DETA: Denoised Task Adaptation for Few-Shot LearningCode1
Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-raysCode1
Xformer: Hybrid X-Shaped Transformer for Image DenoisingCode1
Generative AI for Rapid Diffusion MRI with Improved Image Quality, Reliability and GeneralizabilityCode1
Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass SegmentationCode1
EEG Synthetic Data Generation Using Probabilistic Diffusion ModelsCode1
Learning multi-scale local conditional probability models of imagesCode1
Synthetic ECG Signal Generation using Probabilistic Diffusion ModelsCode1
Entity-Level Text-Guided Image ManipulationCode1
LIT-Former: Linking In-plane and Through-plane Transformers for Simultaneous CT Image Denoising and DeblurringCode1
Unsupervised Out-of-Distribution Detection with Diffusion InpaintingCode1
Simulating analogue film damage to analyse and improve artefact restoration on high-resolution scansCode1
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be ConsistentCode1
MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule GenerationCode1
Boundary Guided Learning-Free Semantic Control with Diffusion ModelsCode1
DiffFashion: Reference-based Fashion Design with Structure-aware Transfer by Diffusion ModelsCode1
Robust Unsupervised StyleGAN Image RestorationCode1
Denoising and Prompt-Tuning for Multi-Behavior RecommendationCode1
Star-Shaped Denoising Diffusion Probabilistic ModelsCode1
Better Diffusion Models Further Improve Adversarial TrainingCode1
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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