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 1876–1900 of 7282 papers

TitleStatusHype
A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image DenoisingCode0
Denoising Bottleneck with Mutual Information Maximization for Video Multimodal FusionCode0
Moment Matching Denoising Gibbs SamplingCode0
Beyond the Visible: Jointly Attending to Spectral and Spatial Dimensions with HSI-Diffusion for the FINCH SpacecraftCode0
Adaptive Quantile Sparse Image (AQuaSI) Prior for Inverse Imaging ProblemsCode0
Denoising Noisy Neural Networks: A Bayesian Approach with CompensationCode0
LIDIA: Lightweight Learned Image Denoising with Instance AdaptationCode0
Low-Complexity Blind Parameter Estimation in Wireless Systems with Noisy Sparse SignalsCode0
Denoising-based Contractive Imitation LearningCode0
Denoising of 3D magnetic resonance images with multi-channel residual learning of convolutional neural networkCode0
Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial DefenseCode0
LoFi: Neural Local Fields for Scalable Image ReconstructionCode0
Low Frequency Adversarial PerturbationCode0
Machine learning based lens-free imaging technique for field-portable cytometryCode0
Denoising autoencoder with modulated lateral connections learns invariant representations of natural imagesCode0
LLNet: A Deep Autoencoder Approach to Natural Low-light Image EnhancementCode0
LMD: Faster Image Reconstruction with Latent Masking DiffusionCode0
Localized Fourier Analysis for Graph Signal ProcessingCode0
Cross-model Back-translated Distillation for Unsupervised Machine TranslationCode0
Denoising Architecture for Unsupervised Anomaly Detection in Time-SeriesCode0
Beyond Human Perception: Understanding Multi-Object World from Monocular ViewCode0
LINN: Lifting Inspired Invertible Neural Network for Image DenoisingCode0
Denoising Prior Driven Deep Neural Network for Image RestorationCode0
Multi-hypotheses Conditioned Point Cloud Diffusion for 3D Human Reconstruction from Occluded ImagesCode0
Denoising and Regularization via Exploiting the Structural Bias of Convolutional GeneratorsCode0
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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