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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2901–2925 of 7282 papers

TitleStatusHype
Event-Customized Image Generation—0
Minmax Trend Filtering: Generalizations of Total Variation Denoising via a Local Minmax/Maxmin Formula—0
Combining Pre- and Post-Demosaicking Noise Removal for RAW Video—0
MDSGen: Fast and Efficient Masked Diffusion Temporal-Aware Transformers for Open-Domain Sound Generation—0
Channel-aware Contrastive Conditional Diffusion for Multivariate Probabilistic Time Series ForecastingCode0
An Improved Variational Method for Image Denoising—0
Denoising with a Joint-Embedding Predictive Architecture—0
Tuning Frequency Bias of State Space Models—0
FabricDiffusion: High-Fidelity Texture Transfer for 3D Garments Generation from In-The-Wild Clothing Images—0
Stochastic Deep Restoration Priors for Imaging Inverse Problems—0
A Real Benchmark Swell Noise Dataset for Performing Seismic Data Denoising via Deep Learning—0
Discrete Copula Diffusion—0
LaDTalk: Latent Denoising for Synthesizing Talking Head Videos with High Frequency Details—0
Generative Precipitation Downscaling using Score-based Diffusion with Wasserstein Regularization—0
Denoising VAE as an Explainable Feature Reduction and Diagnostic Pipeline for Autism Based on Resting state fMRI—0
(Almost) Smooth Sailing: Towards Numerical Stability of Neural Networks Through Differentiable Regularization of the Condition NumberCode0
FreeMask: Rethinking the Importance of Attention Masks for Zero-Shot Video Editing—0
Enhancing GANs with Contrastive Learning-Based Multistage Progressive Finetuning SNN and RL-Based External Optimization—0
Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamicsCode0
COLLAGE: Collaborative Human-Agent Interaction Generation using Hierarchical Latent Diffusion and Language Models—0
Fine-Tuning Hybrid Physics-Informed Neural Networks for Vehicle Dynamics Model Estimation—0
SemiDDM-Weather: A Semi-supervised Learning Framework for All-in-one Adverse Weather RemovalCode0
Efficient Semantic Diffusion Architectures for Model Training on Synthetic EchocardiogramsCode0
A Proximal Modified Quasi-Newton Method for Nonsmooth Regularized Optimization—0
Multi-hypotheses Conditioned Point Cloud Diffusion for 3D Human Reconstruction from Occluded ImagesCode0
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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