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 2701–2725 of 7282 papers

TitleStatusHype
CRISPnet: Color Rendition ISP Net—0
A Split-and-Merge Dictionary Learning Algorithm for Sparse Representation—0
A Fused Deep Denoising Sound Coding Strategy for Bilateral Cochlear Implants—0
Creatively Upscaling Images with Global-Regional Priors—0
Crafting Parts for Expressive Object Composition—0
ASP: Learning to Forget with Adaptive Synaptic Plasticity in Spiking Neural Networks—0
Active contours driven by local and global intensity fitting energy with application to SAR image segmentation and its fast solvers—0
A Spectrum-based Image Denoising Method with Edge Feature Enhancement—0
Covariance Trees for 2D and 3D Processing—0
A Spatial-Temporal Decomposition Based Deep Neural Network for Time Series Forecasting—0
A Framework for CSI-Based Indoor Localization with 1D Convolutional Neural Networks—0
FlowLoss: Dynamic Flow-Conditioned Loss Strategy for Video Diffusion Models—0
Coupling BM3D with directional wavelet packets for image denoising—0
A Single Speech Enhancement Model Unifying Dereverberation, Denoising, Speaker Counting, Separation, and Extraction—0
A Fourier Disparity Layer representation for Light Fields—0
Coupled Analysis Dictionary Learning to inductively learn inversion: Application to real-time reconstruction of Biomedical signals—0
Counting Guidance for High Fidelity Text-to-Image Synthesis—0
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design—0
Robustifying Models Against Adversarial Attacks by Langevin Dynamics—0
A Simple Yet Effective Improvement to the Bilateral Filter for Image Denoising—0
A 51.3 TOPS/W, 134.4 GOPS In-memory Binary Image Filtering in 65nm CMOS—0
CountDiffusion: Text-to-Image Synthesis with Training-Free Counting-Guidance Diffusion—0
A Simple Sparse Denoising Layer for Robust Deep Learning—0
CoT-lized Diffusion: Let's Reinforce T2I Generation Step-by-step—0
A Simple Scalable Neural Networks based Model for Geolocation Prediction in Twitter—0
Show:102550
← PrevPage 109 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