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 1501–1550 of 7282 papers

TitleStatusHype
DCT2net: an interpretable shallow CNN for image denoisingCode1
Less is More: Reweighting Important Spectral Graph Features for RecommendationCode1
Certified Robustness for Large Language Models with Self-DenoisingCode1
Let's Rectify Step by Step: Improving Aspect-based Sentiment Analysis with Diffusion ModelsCode1
From Denoising Training to Test-Time Adaptation: Enhancing Domain Generalization for Medical Image SegmentationCode1
From Denoising to Compressed SensingCode1
DDIM sampling for Generative AIBIM, a faster intelligent structural design frameworkCode1
DDM^2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion ModelsCode1
Reciprocal Attention Mixing Transformer for Lightweight Image RestorationCode1
From Rank Estimation to Rank Approximation: Rank Residual Constraint for Image RestorationCode1
LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World DenoisingCode1
(Certified!!) Adversarial Robustness for Free!Code1
Fully Convolutional Pixel Adaptive Image DenoiserCode1
Galaxy Image Deconvolution for Weak Gravitational Lensing with Unrolled Plug-and-Play ADMMCode1
3DInvNet: A Deep Learning-Based 3D Ground-Penetrating Radar Data InversionCode1
Gabor is Enough: Interpretable Deep Denoising with a Gabor Synthesis Dictionary PriorCode1
FusionINN: Decomposable Image Fusion for Brain Tumor MonitoringCode1
DenoiseRep: Denoising Model for Representation LearningCode1
CERL: A Unified Optimization Framework for Light Enhancement with Realistic NoiseCode1
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-ExpertsCode1
Generative AI for Rapid Diffusion MRI with Improved Image Quality, Reliability and GeneralizabilityCode1
GAN-based Priors for Quantifying UncertaintyCode1
Re-Attentional Controllable Video Diffusion EditingCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
LenslessPiCam: A Hardware and Software Platform for Lensless Computational Imaging with a Raspberry PiCode1
Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detectionCode1
LighTDiff: Surgical Endoscopic Image Low-Light Enhancement with T-DiffusionCode1
LIR: A Lightweight Baseline for Image RestorationCode1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
Deep learning architectural designs for super-resolution of noisy imagesCode1
AIM 2020 Challenge on Learned Image Signal Processing PipelineCode1
Decoder Denoising Pretraining for Semantic SegmentationCode1
Learning to See in the DarkCode1
Refining Generative Process with Discriminator Guidance in Score-based Diffusion ModelsCode1
CDLNet: Robust and Interpretable Denoising Through Deep Convolutional Dictionary LearningCode1
CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and DemosaicingCode1
ACDiT: Interpolating Autoregressive Conditional Modeling and Diffusion TransformerCode1
Deep Image PriorCode1
CCSPNet-Joint: Efficient Joint Training Method for Traffic Sign Detection Under Extreme ConditionsCode1
Learning to Generate Realistic LiDAR Point CloudsCode1
CCDM: Continuous Conditional Diffusion Models for Image GenerationCode1
DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation TrainerCode1
Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial TrainingCode1
Learning to Translate Noise for Robust Image DenoisingCode1
CAT-DM: Controllable Accelerated Virtual Try-on with Diffusion ModelCode1
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Learning to Denoise Raw Mobile UI Layouts for Improving Datasets at ScaleCode1
Learning to Discretize Denoising Diffusion ODEsCode1
Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video DenoisingCode1
Learning to Drop: Robust Graph Neural Network via Topological DenoisingCode1
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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