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 1351–1400 of 7282 papers

TitleStatusHype
FDF: Flexible Decoupled Framework for Time Series Forecasting with Conditional Denoising and Polynomial ModelingCode0
Label-free prediction of fluorescence markers in bovine satellite cells using deep learning—0
The Latent Road to Atoms: Backmapping Coarse-grained Protein Structures with Latent Diffusion—0
Meta-DiffuB: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-ExplorationCode0
DiffImp: Efficient Diffusion Model for Probabilistic Time Series Imputation with Bidirectional Mamba Backbone—0
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation—0
TabSeq: A Framework for Deep Learning on Tabular Data via Sequential OrderingCode1
Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers—0
Stable Diffusion with Continuous-time Neural Network—0
On the Relation Between Linear Diffusion and Power Iteration—0
Beyond Oversmoothing: Evaluating DDPM and MSE for Scalable Speech Synthesis in ASR—0
One Step Diffusion via Shortcut ModelsCode4
Synthetic Augmentation for Anatomical Landmark Localization using DDPMs—0
Evaluating Utility of Memory Efficient Medical Image Generation: A Study on Lung Nodule Segmentation—0
SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video GenerationCode2
MING: A Functional Approach to Learning Molecular Generative Models—0
Constrained Posterior Sampling: Time Series Generation with Hard Constraints—0
Open Materials 2024 (OMat24) Inorganic Materials Dataset and ModelsCode1
From Real Artifacts to Virtual Reference: A Robust Framework for Translating Endoscopic Images—0
A Survey on Deep Tabular Learning—0
DDIL: Diversity Enhancing Diffusion Distillation With Imitation Learning—0
Learning Diffusion Model from Noisy Measurement using Principled Expectation-Maximization Method—0
DreamSteerer: Enhancing Source Image Conditioned Editability using Personalized Diffusion ModelsCode0
Rician Denoising Diffusion Probabilistic Models For Sodium Breast MRI Enhancement—0
Fast Local Neural Regression for Low-Cost, Path Traced Lambertian Global Illumination—0
DRACO: A Denoising-Reconstruction Autoencoder for Cryo-EM—0
Feature-guided score diffusion for sampling conditional densities—0
On the Effectiveness of Dataset Alignment for Fake Image DetectionCode1
Language Model Preference Evaluation with Multiple Weak EvaluatorsCode0
Data-Aware Training Quality Monitoring and Certification for Reliable Deep LearningCode0
DMOSpeech: Direct Metric Optimization via Distilled Diffusion Model in Zero-Shot Speech Synthesis—0
CleanUMamba: A Compact Mamba Network for Speech Denoising using Channel PruningCode1
High-Precision Dichotomous Image Segmentation via Probing Diffusion CapacityCode2
Adaptive Diffusion Terrain Generator for Autonomous Uneven Terrain NavigationCode1
TrajDiffuse: A Conditional Diffusion Model for Environment-Aware Trajectory PredictionCode1
Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion ModelsCode2
MMAR: Towards Lossless Multi-Modal Auto-Regressive Probabilistic Modeling—0
Vision-guided and Mask-enhanced Adaptive Denoising for Prompt-based Image EditingCode0
Variational Diffusion Posterior Sampling with Midpoint GuidanceCode1
Physics-informed AI and ML-based sparse system identification algorithm for discovery of PDE's representing nonlinear dynamic systems—0
Training-Free Adaptive Diffusion with Bounded Difference Approximation StrategyCode2
DuoDiff: Accelerating Diffusion Models with a Dual-Backbone ApproachCode0
Reconstructive Visual Instruction TuningCode2
Quality Prediction of AI Generated Images and Videos: Emerging Trends and Opportunities—0
DiffPO: A causal diffusion model for learning distributions of potential outcomesCode1
Avoiding mode collapse in diffusion models fine-tuned with reinforcement learning—0
Conditional Lagrangian Wasserstein Flow for Time Series Imputation—0
DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation—0
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction—0
MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete DiffusionCode0
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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