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 2601–2650 of 7282 papers

TitleStatusHype
You KAN Do It in a Single Shot: Plug-and-Play Methods with Single-Instance Priors—0
Efficiency Meets Fidelity: A Novel Quantization Framework for Stable Diffusion—0
Echocardiography to Cardiac MRI View Transformation for Real-Time Blind Restoration—0
Diverse Score Distillation—0
CARP: Visuomotor Policy Learning via Coarse-to-Fine Autoregressive Prediction—0
BudgetFusion: Perceptually-Guided Adaptive Diffusion Models—0
Accelerating Video Diffusion Models via Distribution Matching—0
3D-Consistent Image Inpainting with Diffusion Models—0
Adversarial Transferability in Deep Denoising Models: Theoretical Insights and Robustness Enhancement via Out-of-Distribution Typical Set Sampling—0
Enhanced 3D Generation by 2D Editing—0
Tiny Object Detection with Single Point Supervision—0
Enhancing Sample Generation of Diffusion Models using Noise Level Correction—0
Graph with Sequence: Broad-Range Semantic Modeling for Fake News Detection—0
A Comparative Study of Image Denoising Algorithms—0
The Silent Prompt: Initial Noise as Implicit Guidance for Goal-Driven Image Generation—0
Latent Space Characterization of Autoencoder Variants—0
Equivariant Denoisers for Image Restoration—0
A Data-Driven Framework for Discovering Fractional Differential Equations in Complex Systems—0
Deep priors for satellite image restoration with accurate uncertainties—0
Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image—0
Local Curvature Smoothing with Stein's Identity for Efficient Score Matching—0
SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rollout—0
INFP: Audio-Driven Interactive Head Generation in Dyadic Conversations—0
A Noise is Worth Diffusion Guidance—0
Assessing the performance of CT image denoisers using Laguerre-Gauss Channelized Hotelling Observer for lesion detection—0
Imagine360: Immersive 360 Video Generation from Perspective Anchor—0
End-to-end Triple-domain PET Enhancement: A Hybrid Denoising-and-reconstruction Framework for Reconstructing Standard-dose PET Images from Low-dose PET Sinograms—0
UTSD: Unified Time Series Diffusion Model—0
Partially Conditioned Patch Parallelism for Accelerated Diffusion Model Inference—0
Grayscale to Hyperspectral at Any Resolution Using a Phase-Only Lens—0
OmniCreator: Self-Supervised Unified Generation with Universal Editing—0
Diffusion Implicit Policy for Unpaired Scene-aware Motion Synthesis—0
MFTF: Mask-free Training-free Object Level Layout Control Diffusion ModelCode0
Schedule On the Fly: Diffusion Time Prediction for Faster and Better Image Generation—0
NitroFusion: High-Fidelity Single-Step Diffusion through Dynamic Adversarial Training—0
Concept Replacer: Replacing Sensitive Concepts in Diffusion Models via Precision LocalizationCode0
An overview of diffusion models for generative artificial intelligence—0
On the Feature Learning in Diffusion Models—0
A Lesson in Splats: Teacher-Guided Diffusion for 3D Gaussian Splats Generation with 2D Supervision—0
Efficient Off-Grid Bayesian Parameter Estimation for Kronecker-Structured SignalsCode0
Riemannian Denoising Score Matching for Molecular Structure Optimization with Accurate Energy—0
MoTe: Learning Motion-Text Diffusion Model for Multiple Generation Tasks—0
Contextual Checkerboard Denoise -- A Novel Neural Network-Based Approach for Classification-Aware OCT Image DenoisingCode0
Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based ApproachCode0
MSEMG: Surface Electromyography Denoising with a Mamba-based Efficient NetworkCode0
FiRe: Fixed-points of Restoration Priors for Solving Inverse ProblemsCode0
VIPaint: Image Inpainting with Pre-Trained Diffusion Models via Variational Inference—0
Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough?—0
Structured Object Language Modeling (SoLM): Native Structured Objects Generation Conforming to Complex Schemas with Self-Supervised Denoising—0
SOWing Information: Cultivating Contextual Coherence with MLLMs in Image Generation—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