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 7101–7150 of 7282 papers

TitleStatusHype
Controllable Motion Generation via Diffusion Modal CouplingCode0
SaGess: Sampling Graph Denoising Diffusion Model for Scalable Graph GenerationCode0
Averaged Deep Denoisers for Image RegularizationCode0
ERNIE-ViLG 2.0: Improving Text-to-Image Diffusion Model with Knowledge-Enhanced Mixture-of-Denoising-ExpertsCode0
A Novel Truncated Norm Regularization Method for Multi-channel Color Image DenoisingCode0
Towards More Accurate Diffusion Model Acceleration with A Timestep TunerCode0
Improving Chinese Story Generation via Awareness of Syntactic Dependencies and SemanticsCode0
Accelerated Gradient Methods for Sparse Statistical Learning with Nonconvex PenaltiesCode0
Quantum-Inspired Hamiltonian Monte Carlo for Bayesian SamplingCode0
ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge SplittingCode0
TWIST: Two-Way Inter-Label Self-Training for Semi-Supervised 3D Instance SegmentationCode0
Back-Projection based Fidelity Term for Ill-Posed Linear Inverse ProblemsCode0
Mesh Denoising with Facet Graph ConvolutionsCode0
Can learning from natural image denoising be used for seismic data interpolation?Code0
On-the-fly Denoising for Data Augmentation in Natural Language UnderstandingCode0
Meta-DiffuB: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-ExplorationCode0
Estimating network edge probabilities by neighborhood smoothingCode0
Compensation Sampling for Improved Convergence in Diffusion ModelsCode0
Estimating Probability Densities with Transformer and Denoising DiffusionCode0
SAM-PD: How Far Can SAM Take Us in Tracking and Segmenting Anything in Videos by Prompt DenoisingCode0
On the Importance of Denoising when Learning to Compress ImagesCode0
On the Importance of Noise Scheduling for Diffusion ModelsCode0
DeepRED: Deep Image Prior Powered by REDCode0
Metaphor Detection with Effective Context DenoisingCode0
Quaternion Convolutional Neural NetworksCode0
Deep Learning-Based Channel EstimationCode0
Evaluating Unsupervised Denoising Requires Unsupervised MetricsCode0
Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled DataCode0
An Underparametrized Deep Decoder Architecture for Graph SignalsCode0
Improving Hypernymy Extraction with Distributional Semantic ClassesCode0
Complex Image Generation SwinTransformer Network for Audio DenoisingCode0
The Intel Neuromorphic DNS ChallengeCode0
Event-based Camera Simulation using Monte Carlo Path Tracing with Adaptive DenoisingCode0
Lightweight network towards real-time image denoising on mobile devicesCode0
MFM-DA: Instance-Aware Adaptor and Hierarchical Alignment for Efficient Domain Adaptation in Medical Foundation ModelsCode0
Event-driven Video Frame SynthesisCode0
Deep learning-based deconvolution for interferometric radio transient reconstructionCode0
On the Noise Sensitivity of the Randomized SVDCode0
MFTF: Mask-free Training-free Object Level Layout Control Diffusion ModelCode0
Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated CasesCode0
Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspectiveCode0
Balancing the Style-Content Trade-Off in Sentiment Transfer Using Polarity-Aware DenoisingCode0
Zero-Shot Denoising for Fluorescence Lifetime Imaging Microscopy with Intensity-Guided LearningCode0
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMMCode0
On the Perturbed States for Transformed Input-robust Reinforcement LearningCode0
RH-Net: Improving Neural Relation Extraction via Reinforcement Learning and Hierarchical Relational SearchingCode0
Towards Open-world Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising ApproachCode0
Improving Robustness to Model Inversion Attacks via Sparse Coding ArchitecturesCode0
ExactDreamer: High-Fidelity Text-to-3D Content Creation via Exact Score MatchingCode0
Microscopy Image Restoration with Deep Wiener-Kolmogorov filtersCode0
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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