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 2851–2900 of 7282 papers

TitleStatusHype
Finding Local Diffusion Schrödinger Bridge using Kolmogorov-Arnold NetworkCode0
FlexControl: Computation-Aware ControlNet with Differentiable Router for Text-to-Image GenerationCode0
DiffLLE: Diffusion-guided Domain Calibration for Unsupervised Low-light Image Enhancement—0
Calliffusion: Chinese Calligraphy Generation and Style Transfer with Diffusion Modeling—0
DiffKAN-Inpainting: KAN-based Diffusion model for brain tumor inpainting—0
Calibration of depth cameras using denoised depth images—0
CAGE: Controllable Articulation GEneration—0
CaDM: Codec-aware Diffusion Modeling for Neural-enhanced Video Streaming—0
A Deep Learning based Detection Method for Combined Integrity-Availability Cyber Attacks in Power System—0
DiffImp: Efficient Diffusion Model for Probabilistic Time Series Imputation with Bidirectional Mamba Backbone—0
DiffI2I: Efficient Diffusion Model for Image-to-Image Translation—0
DiffHuman: Probabilistic Photorealistic 3D Reconstruction of Humans—0
Cache Me if You Can: Accelerating Diffusion Models through Block Caching—0
DiffHand: End-to-End Hand Mesh Reconstruction via Diffusion Models—0
DiffGaze: A Diffusion Model for Continuous Gaze Sequence Generation on 360° Images—0
DiffGAP: A Lightweight Diffusion Module in Contrastive Space for Bridging Cross-Model Gap—0
A Neural Denoising Vocoder for Clean Waveform Generation from Noisy Mel-Spectrogram based on Amplitude and Phase Predictions—0
A Deep Learning Approach to Structured Signal Recovery—0
Accurate and Lightweight Image Super-Resolution with Model-Guided Deep Unfolding Network—0
DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs—0
DiffGANPaint: Fast Inpainting Using Denoising Diffusion GANs—0
DiffGAN-F2S: Symmetric and Efficient Denoising Diffusion GANs for Structural Connectivity Prediction from Brain fMRI—0
DiffForensics: Leveraging Diffusion Prior to Image Forgery Detection and Localization—0
An Ensemble Model for Distorted Images in Real Scenarios—0
MDiff-FMT: Morphology-aware Diffusion Model for Fluorescence Molecular Tomography with Small-scale Datasets—0
DiffFlow: A Unified SDE Framework for Score-Based Diffusion Models and Generative Adversarial Networks—0
Differentially Private Federated Learning of Diffusion Models for Synthetic Tabular Data Generation—0
A Deep Learning Approach to Predicting Collateral Flow in Stroke Patients Using Radiomic Features from Perfusion Images—0
Differentiable Programming for Piecewise Polynomial Functions—0
Differentiable Forward and Backward Fixed-Point Iteration Layers—0
Differentiable Electron Microscopy Simulation: Methods and Applications for Visualization—0
DiffECG: A Versatile Probabilistic Diffusion Model for ECG Signals Synthesis—0
Burst Denoising via Temporally Shifted Wavelet Transforms—0
An End-to-End Deep Learning Architecture for Classification of Malware’s Binary Content—0
A Deep Learning Approach to Data-driven Parameterizations for Statistical Parametric Speech Synthesis—0
ACCORD: Alleviating Concept Coupling through Dependence Regularization for Text-to-Image Diffusion Personalization—0
DiffDreamer: Towards Consistent Unsupervised Single-view Scene Extrapolation with Conditional Diffusion Models—0
DiffDesign: Controllable Diffusion with Meta Prior for Efficient Interior Design Generation—0
DiffDenoise: Self-Supervised Medical Image Denoising with Conditional Diffusion Models—0
Burger: Robust Graph Denoising-augmentation Fusion and Multi-semantic Modeling in Social Recommendation—0
Diff-CAPTCHA: An Image-based CAPTCHA with Security Enhanced by Denoising Diffusion Model—0
BuilDiff: 3D Building Shape Generation using Single-Image Conditional Point Cloud Diffusion Models—0
A Deep Generative Model for the Simulation of Discrete Karst Networks—0
DiffCAP: Diffusion-based Cumulative Adversarial Purification for Vision Language Models—0
DiffBrush:Just Painting the Art by Your Hands—0
BudgetFusion: Perceptually-Guided Adaptive Diffusion Models—0
DiffBFR: Bootstrapping Diffusion Model Towards Blind Face Restoration—0
BTS: Back TranScription for Speech-to-Text Post-Processor using Text-to-Speech-to-Text—0
Diff3DETR:Agent-based Diffusion Model for Semi-supervised 3D Object Detection—0
An Empirical Study of ADMM for Nonconvex Problems—0
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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