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 951–1000 of 7282 papers

TitleStatusHype
Block-wise Minimization-Majorization algorithm for Huber's criterion: sparse learning and applicationsCode1
DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion ModelCode1
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic ModelsCode1
An Analysis and Implementation of the HDR+ Burst Denoising MethodCode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
Are Diffusion Models Vision-And-Language Reasoners?Code1
Adversarial Distortion Learning for Medical Image DenoisingCode1
Learnability Enhancement for Low-light Raw Denoising: Where Paired Real Data Meets Noise ModelingCode1
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform GenerationCode1
Are Deep Neural Architectures Losing Information? Invertibility Is IndispensableCode1
Learning Enriched Features for Real Image Restoration and EnhancementCode1
Learning from Rules Generalizing Labeled ExemplarsCode1
Boosting of Implicit Neural Representation-based Image DenoiserCode1
Learning Medical Image Denoising with Deep Dynamic Residual Attention NetworkCode1
Learning Robust Recommender from Noisy Implicit FeedbackCode1
Learning Self-prior for Mesh Denoising using Dual Graph Convolutional NetworksCode1
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud CompletionCode1
Learning to Denoise Raw Mobile UI Layouts for Improving Datasets at ScaleCode1
Anatomy Completor: A Multi-class Completion Framework for 3D Anatomy ReconstructionCode1
Learning to Drop: Robust Graph Neural Network via Topological DenoisingCode1
DiffFashion: Reference-based Fashion Design with Structure-aware Transfer by Diffusion ModelsCode1
A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising ModelsCode1
Boundary Guided Learning-Free Semantic Control with Diffusion ModelsCode1
Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial TrainingCode1
DialogLM: Pre-trained Model for Long Dialogue Understanding and SummarizationCode1
DFormer: Diffusion-guided Transformer for Universal Image SegmentationCode1
A Conditional Diffusion Model for Electrical Impedance Tomography Image ReconstructionCode1
Legacy Photo Editing with Learned Noise PriorCode1
Let's Rectify Step by Step: Improving Aspect-based Sentiment Analysis with Diffusion ModelsCode1
lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systemsCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein TracesCode1
AR-Diffusion: Auto-Regressive Diffusion Model for Text GenerationCode1
AR-DAE: Towards Unbiased Neural Entropy Gradient EstimationCode1
Adversarial Counterfactual Visual ExplanationsCode1
LIPT: Latency-aware Image Processing TransformerCode1
LIR: A Lightweight Baseline for Image RestorationCode1
Listening to Sounds of Silence for Speech DenoisingCode1
Lite Audio-Visual Speech EnhancementCode1
LIT-Former: Linking In-plane and Through-plane Transformers for Simultaneous CT Image Denoising and DeblurringCode1
3D Shape Generation and Completion through Point-Voxel DiffusionCode1
A Conditional Denoising Diffusion Probabilistic Model for Point Cloud UpsamplingCode1
Accelerated MRI with Un-trained Neural NetworksCode1
Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual LossCode1
Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image RestorationCode1
Lung-DDPM: Semantic Layout-guided Diffusion Models for Thoracic CT Image SynthesisCode1
M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI researchCode1
MAAD: A Model and Dataset for "Attended Awareness" in DrivingCode1
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game EncodingCode1
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion DelineationCode1
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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