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 5901–5950 of 7282 papers

TitleStatusHype
Cross-denoising Network against Corrupted Labels in Medical Image Segmentation with Domain Shift—0
Cross-domain feature disentanglement for interpretable modeling of tumor microenvironment impact on drug response—0
Cross-Domain Image Conversion by CycleDM—0
Cross-domain Iterative Network for Simultaneous Denoising, Limited-angle Reconstruction, and Attenuation Correction of Low-dose Cardiac SPECT—0
Cross-Domain Lossy Compression as Optimal Transport with an Entropy Bottleneck—0
Cross-domain Recommendation via Deep Domain Adaptation—0
Cross-Frequency Implicit Neural Representation with Self-Evolving Parameters—0
Crossfusor: A Cross-Attention Transformer Enhanced Conditional Diffusion Model for Car-Following Trajectory Prediction—0
Cross-Image Attention for Zero-Shot Appearance Transfer—0
Sparse Factorization Layers for Neural Networks with Limited Supervision—0
Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study—0
CrossMatch: Source-Free Domain Adaptive Semantic Segmentation via Cross-Modal Consistency Training—0
Cross-Modal Denoising: A Novel Training Paradigm for Enhancing Speech-Image Retrieval—0
Cross-Patch Graph Convolutional Network for Image Denoising—0
Cross-Scale Residual Network for Multiple Tasks:Image Super-resolution, Denoising, and Deblocking—0
Analyzing the Weighted Nuclear Norm Minimization and Nuclear Norm Minimization based on Group Sparse Representation—0
CrossViewDiff: A Cross-View Diffusion Model for Satellite-to-Street View Synthesis—0
Analyzing noise in autoencoders and deep networks—0
Crowd Counting in Harsh Weather using Image Denoising with Pix2Pix GANs—0
CrowdMoGen: Zero-Shot Text-Driven Collective Motion Generation—0
Cryo-Electron Microscopy Image Analysis Using Multi-Frequency Vector Diffusion Maps—0
Sparse Filtered SIRT for Electron Tomography—0
CSI-fingerprinting Indoor Localization via Attention-Augmented Residual Convolutional Neural Network—0
CSI-PPPNet: A One-Sided One-for-All Deep Learning Framework for Massive MIMO CSI Feedback—0
CS-PCN: Context-Space Progressive Collaborative Network for Image Denoising—0
Sparse High-Dimensional Linear Regression. Algorithmic Barriers and a Local Search Algorithm—0
CT Image Denoising with Perceptive Deep Neural Networks—0
CTLformer: A Hybrid Denoising Model Combining Convolutional Layers and Self-Attention for Enhanced CT Image Reconstruction—0
Ctrl-Z Sampling: Diffusion Sampling with Controlled Random Zigzag Explorations—0
CT Synthesis with Conditional Diffusion Models for Abdominal Lymph Node Segmentation—0
Parallel Diffusion Model-based Sparse-view Cone-beam Breast CT—0
CUNI Submission to MT4All Shared Task—0
Analyzing Neural Network-Based Generative Diffusion Models through Convex Optimization—0
Sparse Measurement Medical CT Reconstruction using Multi-Fused Block Matching Denoising Priors—0
SparseMeXT Unlocking the Potential of Sparse Representations for HD Map Construction—0
Sparse Mixture-of-Experts for Non-Uniform Noise Reduction in MRI Images—0
Sparse Models for Machine Learning—0
Sparse Nonnegative Tensor Factorization and Completion with Noisy Observations—0
CWGAN-GP Augmented CAE for Jamming Detection in 5G-NR in Non-IID Datasets—0
Cycle3D: High-quality and Consistent Image-to-3D Generation via Generation-Reconstruction Cycle—0
Self-Consistent Nested Diffusion Bridge for Accelerated MRI Reconstruction—0
Cycle-Constrained Adversarial Denoising Convolutional Network for PET Image Denoising: Multi-Dimensional Validation on Large Datasets with Reader Study and Real Low-Dose Data—0
Cycle-free CycleGAN using Invertible Generator for Unsupervised Low-Dose CT Denoising—0
Cycle-guided Denoising Diffusion Probability Model for 3D Cross-modality MRI Synthesis—0
Sparse Recovery and Dictionary Learning from Nonlinear Compressive Measurements—0
Sparse Representation and Non-Negative Matrix Factorization for image denoise—0
Sparse Signal Subspace Decomposition Based on Adaptive Over-complete Dictionary—0
Sparse Subspace Denoising for Image Manifolds—0
Analyzing and Improving Model Collapse in Rectified Flow Models—0
Various Total Variation for Snapshot Video Compressive Imaging—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