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 26–50 of 7282 papers

TitleStatusHype
DiffuCoder: Understanding and Improving Masked Diffusion Models for Code GenerationCode4
Time-series surrogates from energy consumers generated by machine learning approaches for long-term forecasting scenarios—0
NAADA: A Noise-Aware Attention Denoising Autoencoder for Dental Panoramic Radiographs—0
Continuous-variable Quantum Diffusion Model for State Generation and Restoration—0
Elucidated Rolling Diffusion Models for Probabilistic Weather ForecastingCode1
Local Averaging Accurately Distills Manifold Structure From Noisy Data—0
EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation—0
Exploring Strategies for Personalized Radiation Therapy Part II Predicting Tumor Drift Patterns with Diffusion Models—0
Visual-Instructed Degradation Diffusion for All-in-One Image RestorationCode1
DiffO: Single-step Diffusion for Image Compression at Ultra-Low BitratesCode1
Learning Multi-scale Spatial-frequency Features for Image Denoising—0
FlowRAM: Grounding Flow Matching Policy with Region-Aware Mamba Framework for Robotic Manipulation—0
EDNet: A Distortion-Agnostic Speech Enhancement Framework with Gating Mamba Mechanism and Phase Shift-Invariant Training—0
Fiber Signal Denoising Algorithm using Hybrid Deep Learning Networks—0
D2Diff : A Dual Domain Diffusion Model for Accurate Multi-Contrast MRI SynthesisCode0
A Real-time Endoscopic Image Denoising System—0
Generative thermodynamic computing—0
CWGAN-GP Augmented CAE for Jamming Detection in 5G-NR in Non-IID Datasets—0
Demonstrating Superresolution in Radar Range Estimation Using a Denoising Autoencoder—0
Optimization-Based Image Restoration under Implementation Constraints in Optical Analog Circuits—0
A Comparative Evaluation of Deep Learning Models for Speech Enhancement in Real-World Noisy Environments—0
Iterative Camera-LiDAR Extrinsic Optimization via Surrogate DiffusionCode0
DiffusionBlocks: Blockwise Training for Generative Models via Score-Based Diffusion—0
Cost-Aware Routing for Efficient Text-To-Image Generation—0
Exploring Diffusion with Test-Time Training on Efficient Image Restoration—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