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 2351–2375 of 7282 papers

TitleStatusHype
Deep learning denoising for EOG artifacts removal from EEG signals—0
Deep learning denoiser assisted roughness measurements extraction from thin resists with low Signal-to-Noise Ratio(SNR) SEM images: analysis with SMILE—0
Auxiliary Features-Guided Super Resolution for Monte Carlo Rendering—0
Deep Learning CT Image Restoration using System Blur and Noise Models—0
Auto Tensor Singular Value Thresholding: A Non-Iterative and Rank-Free Framework for Tensor Denoising—0
Align-A-Video: Deterministic Reward Tuning of Image Diffusion Models for Consistent Video Editing—0
Adaptive Direction-Guided Structure Tensor Total Variation—0
Enhancing Real-World Active Speaker Detection with Multi-Modal Extraction Pre-Training—0
Enhancing super-resolution ultrasound localisation through multi-frame deconvolution exploiting spatiotemporal coherence—0
Deep Learning-based Symbolic Indoor Positioning using the Serving eNodeB—0
Autoregressive Score Matching—0
A lightweight convolutional neural network for image denoising with fine details preservation capability—0
Deep learning-based statistical noise reduction for multidimensional spectral data—0
Deep Learning-based Modulation Detection for NOMA Systems—0
Autoregressive Moving Average Graph Filtering—0
A Light Label Denoising Method with the Internal Data Guidance—0
Deep Learning-Based Extended Target Tracking in ISAC Systems—0
Deep learning based electrical noise removal enables high spectral optoacoustic contrast in deep tissue—0
Deep Learning-based Denoising of Mammographic Images using Physics-driven Data Augmentation—0
Autonomous Point Cloud Segmentation for Power Lines Inspection in Smart Grid—0
A lifted Bregman strategy for training unfolded proximal neural network Gaussian denoisers—0
Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evolving Data Streams—0
Adaptive diffusion constrained total variation scheme with application to `cartoon + texture + edge' image decomposition—0
Deep Learning Based Channel Covariance Matrix Estimation with User Location and Scene Images—0
Deep Learning Architecture for Motor Imaged Words—0
Show:102550
← PrevPage 95 of 292Next →
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