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 5276–5300 of 7282 papers

TitleStatusHype
A Possible Converter to Denoise the Images of Exoplanet Candidates through Machine Learning Techniques—0
Application of Bounded Total Variation Denoising in Urban Traffic Analysis—0
Application of Joint Notch Filtering and Wavelet Transform for Enhanced Powerline Interference Removal in Atrial Fibrillation Electrograms—0
Applications of Modular Co-Design for De Novo 3D Molecule Generation—0
Approximate Caching for Efficiently Serving Diffusion Models—0
Approximate Grassmannian Intersections: Subspace-Valued Subspace Learning—0
Approximately Invertible Neural Network for Learned Image Compression—0
Approximate Nearest Neighbor Fields in Video—0
A Practical Gated Recurrent Transformer Network Incorporating Multiple Fusions for Video Denoising—0
A Preliminary Exploration Towards General Image Restoration—0
A Primal-Dual Algorithm for Higher-Order Multilabel Markov Random Fields—0
A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction—0
A Priori Denoising Strategies for Sparse Identification of Nonlinear Dynamical Systems: A Comparative Study—0
A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing—0
A Proximal Modified Quasi-Newton Method for Nonsmooth Regularized Optimization—0
APT: Adaptive Personalized Training for Diffusion Models with Limited Data—0
A qualitative investigation of optical flow algorithms for video denoising—0
A quality assurance framework for real-time monitoring of deep learning segmentation models in radiotherapy—0
AquaSignal: An Integrated Framework for Robust Underwater Acoustic Analysis—0
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation—0
Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decoder—0
Signal Recovery with Non-Expansive Generative Network Priors—0
Signature of Geometric Centroids for 3D Local Shape Description and Partial Shape Matching—0
A Real Benchmark Swell Noise Dataset for Performing Seismic Data Denoising via Deep Learning—0
A Real-time Endoscopic Image Denoising System—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