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 2951–3000 of 7282 papers

TitleStatusHype
A Large Language Model and Denoising Diffusion Framework for Targeted Design of Microstructures with Commands in Natural Language—0
Anisotropic Diffusion Probabilistic Model for Imbalanced Image Classification—0
High-dimensional learning of narrow neural networks—0
Nonlinear Inverse Design of Mechanical Multi-Material Metamaterials Enabled by Video Denoising Diffusion and Structure Identifier—0
PTQ4ADM: Post-Training Quantization for Efficient Text Conditional Audio Diffusion Models—0
DS2TA: Denoising Spiking Transformer with Attenuated Spatiotemporal Attention—0
Denoising Reuse: Exploiting Inter-frame Motion Consistency for Efficient Video Latent Generation—0
When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising RecommendationCode0
Unrolled denoising networks provably learn optimal Bayesian inference—0
Denoising diffusion models for high-resolution microscopy image restoration—0
Agent Aggregator with Mask Denoise Mechanism for Histopathology Whole Slide Image Analysis—0
GUNet: A Graph Convolutional Network United Diffusion Model for Stable and Diversity Pose Generation—0
Noise-aware Dynamic Image Denoising and Positron Range Correction for Rubidium-82 Cardiac PET Imaging via Self-supervision—0
Enhanced segmentation of femoral bone metastasis in CT scans of patients using synthetic data generation with 3D diffusion models—0
Edge-based Denoising Image Compression—0
Adaptive Segmentation-Based Initialization for Steered Mixture of Experts Image Regression—0
Taming Diffusion Models for Image Restoration: A Review—0
Exploring Prediction Targets in Masked Pre-Training for Speech Foundation Models—0
Large Language Model Enhanced Hard Sample Identification for Denoising Recommendation—0
Self-Supervised Elimination of Non-Independent Noise in Hyperspectral Imaging—0
BNEM: A Boltzmann Sampler Based on Bootstrapped Noised Energy MatchingCode0
Schrödinger Bridge Flow for Unpaired Data Translation—0
Robust Training of Neural Networks at Arbitrary Precision and Sparsity—0
ManiDext: Hand-Object Manipulation Synthesis via Continuous Correspondence Embeddings and Residual-Guided Diffusion—0
E1 TTS: Simple and Fast Non-Autoregressive TTS—0
Using Convolutional Neural Networks for Denoising and Deblending of Marine Seismic Data—0
Sub-graph Based Diffusion Model for Link Prediction—0
Pushing Joint Image Denoising and Classification to the Edge—0
Cross-conditioned Diffusion Model for Medical Image to Image Translation—0
MambaFoley: Foley Sound Generation using Selective State-Space ModelsCode0
Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control—0
Quaternion Nuclear Norm minus Frobenius Norm Minimization for color image reconstruction—0
Critically Damped Third-Order Langevin Dynamics—0
Localized Schrödinger Bridge Sampler—0
LoRID: Low-Rank Iterative Diffusion for Adversarial Purification—0
MagicStyle: Portrait Stylization Based on Reference Image—0
Diffusion-Based Image-to-Image Translation by Noise Correction via Prompt Interpolation—0
FreeEnhance: Tuning-Free Image Enhancement via Content-Consistent Noising-and-Denoising Process—0
Exploring User-level Gradient Inversion with a Diffusion Prior—0
AdvLogo: Adversarial Patch Attack against Object Detectors based on Diffusion Models—0
ART: Artifact Removal Transformer for Reconstructing Noise-Free Multichannel Electroencephalographic Signals—0
Efficient and Unbiased Sampling of Boltzmann Distributions via Consistency Models—0
Structure Modeling Activation Free Fourier Network for Spacecraft Image DenoisingCode0
Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning—0
Constructing an Interpretable Deep Denoiser by Unrolling Graph Laplacian Regularizer—0
A Practical Gated Recurrent Transformer Network Incorporating Multiple Fusions for Video Denoising—0
CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty QuantificationCode0
pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning—0
STLLM-DF: A Spatial-Temporal Large Language Model with Diffusion for Enhanced Multi-Mode Traffic System Forecasting—0
Physics-augmented Deep Learning with Adversarial Domain Adaptation: Applications to STM Image Denoising—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