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 801–850 of 7282 papers

TitleStatusHype
ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT DenoisingCode1
Denoising Diffusion Step-aware ModelsCode1
Denoising Diffusion Probabilistic Models to Predict the Density of Molecular CloudsCode1
Denoising Diffusion Probabilistic Models for Generation of Realistic Fully-Annotated Microscopy Image Data SetsCode1
Convolutional Proximal Neural Networks and Plug-and-Play AlgorithmsCode1
Denoising Diffusion Recommender ModelCode1
Adaptive Differential Denoising for Respiratory Sounds ClassificationCode1
Denoising: from classical methods to deep CNNsCode1
EulerMormer: Robust Eulerian Motion Magnification via Dynamic Filtering within TransformerCode1
Modeling State Shifting via Local-Global Distillation for Event-Frame Gaze TrackingCode1
3D^2-Actor: Learning Pose-Conditioned 3D-Aware Denoiser for Realistic Gaussian Avatar ModelingCode1
Autoregressive Diffusion Model for Graph GenerationCode1
Denoising Implicit Feedback for RecommendationCode1
Denoising Higher-order Moments for Blind Digital Modulation Identification in Multiple-antenna SystemsCode1
Exploring Generative Neural Temporal Point ProcessCode1
Convergence Guarantees for Non-Convex Optimisation with Cauchy-Based PenaltiesCode1
Enhancing Robustness Against Adversarial Examples in Network Intrusion Detection SystemsCode1
A Variational Perspective on Solving Inverse Problems with Diffusion ModelsCode1
Adaptive Diffusion Terrain Generator for Autonomous Uneven Terrain NavigationCode1
Diffiner: A Versatile Diffusion-based Generative Refiner for Speech EnhancementCode1
Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual PerceptionCode1
Denoising Normalizing FlowCode1
ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial DefenseCode1
Denoising Point Clouds in Latent Space via Graph Convolution and Invertible Neural NetworkCode1
A cross Transformer for image denoisingCode1
A zero-inflated gamma model for deconvolved calcium imaging tracesCode1
Artifact Restoration in Histology Images with Diffusion Probabilistic ModelsCode1
Controlling Latent Diffusion Using Latent CLIPCode1
Backpropagation-Friendly EigendecompositionCode1
Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time StepsCode1
Entity-Level Text-Guided Image ManipulationCode1
4DenoiseNet: Adverse Weather Denoising from Adjacent Point CloudsCode1
Enhancing Intrinsic Adversarial Robustness via Feature Pyramid DecoderCode1
DenoMamba: A fused state-space model for low-dose CT denoisingCode1
3D Brain and Heart Volume Generative Models: A SurveyCode1
Enhancing Creative Generation on Stable Diffusion-based ModelsCode1
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion DelineationCode1
Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data HidingCode1
EchoNet-Quality: Denoising Echocardiograms via Deep Generative Modeling of Ultrasound NoiseCode1
Enhancing MMDiT-Based Text-to-Image Models for Similar Subject GenerationCode1
Entropy-driven Sampling and Training Scheme for Conditional Diffusion GenerationCode1
Homotopic Gradients of Generative Density Priors for MR Image ReconstructionCode1
Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time AdaptationCode1
DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly DetectionCode1
Continuous Speculative Decoding for Autoregressive Image GenerationCode1
HQ-50K: A Large-scale, High-quality Dataset for Image RestorationCode1
Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion ModelsCode1
Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image RestorationCode1
Continual Learning of Diffusion Models with Generative DistillationCode1
Argmax Flows and Multinomial Diffusion: Learning Categorical DistributionsCode1
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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