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 1576–1600 of 7282 papers

TitleStatusHype
Deep Denoising For Scientific Discovery: A Case Study In Electron MicroscopyCode1
Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inferenceCode1
Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting SurfacesCode1
CAT-DM: Controllable Accelerated Virtual Try-on with Diffusion ModelCode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
Point Cloud Denoising via Momentum Ascent in Gradient FieldsCode1
Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud LearningCode1
DiffFashion: Reference-based Fashion Design with Structure-aware Transfer by Diffusion ModelsCode1
Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEGCode1
Deep Diversity-Enhanced Feature Representation of Hyperspectral ImagesCode1
Predictive microstructure image generation using denoising diffusion probabilistic modelsCode1
DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion ModelCode1
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory PredictionCode1
AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool UseCode1
Deep Energy Estimator NetworksCode1
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic ModelsCode1
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform GenerationCode1
Adaptive Deep PnP Algorithm for Video Snapshot Compressive ImagingCode1
Probabilistic AutoencoderCode1
DiffDA: a Diffusion Model for Weather-scale Data AssimilationCode1
Diff-IP2D: Diffusion-Based Hand-Object Interaction Prediction on Egocentric VideosCode1
DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging LoadCode1
Progressive Joint Low-light Enhancement and Noise Removal for Raw ImagesCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
DFormer: Diffusion-guided Transformer for Universal Image SegmentationCode1
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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