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

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Showing 1101–1150 of 7282 papers

TitleStatusHype
Diffusion Action SegmentationCode1
Efficient View Synthesis and 3D-based Multi-Frame Denoising with Multiplane Feature RepresentationsCode1
Masked Autoencoders as Image ProcessorsCode1
Real-time Controllable Denoising for Image and VideoCode1
WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion ModelsCode1
4D Facial Expression Diffusion ModelCode1
Memory-Efficient 3D Denoising Diffusion Models for Medical Image ProcessingCode1
DiffTAD: Temporal Action Detection with Proposal Denoising DiffusionCode1
Seer: Language Instructed Video Prediction with Latent Diffusion ModelsCode1
Spatially Adaptive Self-Supervised Learning for Real-World Image DenoisingCode1
Toward DNN of LUTs: Learning Efficient Image Restoration with Multiple Look-Up TablesCode1
End-to-End Diffusion Latent Optimization Improves Classifier GuidanceCode1
Pix2Video: Video Editing using Image DiffusionCode1
E-MLB: Multilevel Benchmark for Event-Based Camera DenoisingCode1
Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image RestorationCode1
Discovering Interpretable Directions in the Semantic Latent Space of Diffusion ModelsCode1
Localizing Object-level Shape Variations with Text-to-Image Diffusion ModelsCode1
Diff-UNet: A Diffusion Embedded Network for Volumetric SegmentationCode1
Denoising Diffusion Autoencoders are Unified Self-supervised LearnersCode1
Data-Centric Learning from Unlabeled Graphs with Diffusion ModelCode1
Adversarial Counterfactual Visual ExplanationsCode1
Hybrid Spectral Denoising Transformer with Guided AttentionCode1
Denoising Diffusion Post-Processing for Low-Light Image EnhancementCode1
Efficient Diffusion Training via Min-SNR Weighting StrategyCode1
DS-Fusion: Artistic Typography via Discriminated and Stylized DiffusionCode1
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