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 2701–2750 of 7282 papers

TitleStatusHype
Frequency-Aware Guidance for Blind Image Restoration via Diffusion Models—0
Posterior Sampling for Random Noise Attenuation via Score-based Generative ModelsCode0
KAN/MultKAN with Physics-Informed Spline fitting (KAN-PISF) for ordinary/partial differential equation discovery of nonlinear dynamic systems—0
Dataset Distillers Are Good Label Denoisers In the WildCode0
MSSIDD: A Benchmark for Multi-Sensor DenoisingCode0
Controlling Diversity at Inference: Guiding Diffusion Recommender Models with Targeted Category PreferencesCode0
Time Step Generating: A Universal Synthesized Deepfake Image DetectorCode0
Neighboring Slice Noise2Noise: Self-Supervised Medical Image Denoising from Single Noisy Image Volume—0
GeomCLIP: Contrastive Geometry-Text Pre-training for MoleculesCode0
MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious CorrelationsCode0
Test-time Conditional Text-to-Image Synthesis Using Diffusion Models—0
Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolution—0
Probabilistic Prior Driven Attention Mechanism Based on Diffusion Model for Imaging Through Atmospheric Turbulence—0
Learning Generalizable 3D Manipulation With 10 DemonstrationsCode0
Imagine-2-Drive: Leveraging High-Fidelity World Models via Multi-Modal Diffusion Policies—0
Enhancing Diffusion Posterior Sampling for Inverse Problems by Integrating Crafted Measurements—0
DR-BFR: Degradation Representation with Diffusion Models for Blind Face Restoration—0
ColorEdit: Training-free Image-Guided Color editing with diffusion model—0
Graph Neural Networks and Differential Equations: A hybrid approach for data assimilation of fluid flows—0
DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation—0
VidMan: Exploiting Implicit Dynamics from Video Diffusion Model for Effective Robot Manipulation—0
A survey of probabilistic generative frameworks for molecular simulationsCode0
GAN-Based Architecture for Low-dose Computed Tomography Imaging Denoising—0
Video Denoising in Fluorescence Guided Surgery—0
EEG-Based Speech Decoding: A Novel Approach Using Multi-Kernel Ensemble Diffusion Models—0
Iterative tomographic reconstruction with TV prior for low-dose CBCT dental imaging—0
DiffRoad: Realistic and Diverse Road Scenario Generation for Autonomous Vehicle Testing—0
Confidence-aware Denoised Fine-tuning of Off-the-shelf Models for Certified RobustnessCode0
DNN Task Assignment in UAV Networks: A Generative AI Enhanced Multi-Agent Reinforcement Learning Approach—0
Explainable Deep Learning Framework for SERS Bio-quantification—0
SoundSil-DS: Deep Denoising and Segmentation of Sound-field Images with SilhouettesCode0
Efficient Denoising Method to Improve The Resolution of Satellite Images—0
White-Box Diffusion Transformer for single-cell RNA-seq generationCode0
MRI denoising with a non-blind deep complex-valued convolutional neural network—0
PLM-Based Discrete Diffusion Language Models with Entropy-Adaptive Gibbs Sampling—0
DDIM-Driven Coverless Steganography Scheme with Real Key—0
An ambient denoising method based on multi-channel non-negative matrix factorization for wheezing detection—0
Adaptive Whole-Body PET Image Denoising Using 3D Diffusion Models with ControlNet—0
UnDIVE: Generalized Underwater Video Enhancement Using Generative PriorsCode0
Untrained Perceptual Loss for image denoising of line-like structures in MR images—0
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models—0
Nonperfused Retinal Capillaries -- A New Method Developed on OCT and OCTA—0
DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion—0
LoFi: Neural Local Fields for Scalable Image ReconstructionCode0
Quantum Diffusion Models for Few-Shot Learning—0
ADMIRE: a locally adaptive single-image, non-uniformity correction and denoising algorithm: application to uncooled IR camera—0
Gradient-Guided Conditional Diffusion Models for Private Image Reconstruction: Analyzing Adversarial Impacts of Differential Privacy and Denoising—0
Two-Stage Pretraining for Molecular Property Prediction in the Wild—0
SynthSet: Generative Diffusion Model for Semantic Segmentation in Precision AgricultureCode0
Adaptive Caching for Faster Video Generation with Diffusion Transformers—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