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

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Showing 626–650 of 7282 papers

TitleStatusHype
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-ExpertsCode1
DiffTAD: Temporal Action Detection with Proposal Denoising DiffusionCode1
DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic ModelCode1
DiffSim: Taming Diffusion Models for Evaluating Visual SimilarityCode1
DiffSF: Diffusion Models for Scene Flow EstimationCode1
DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion ModelsCode1
Diff-Reg v1: Diffusion Matching Model for Registration ProblemCode1
Ab-initio Contrast Estimation and Denoising of Cryo-EM ImagesCode1
DiffSDS: A language diffusion model for protein backbone inpainting under geometric conditions and constraintsCode1
DiffStyler: Controllable Dual Diffusion for Text-Driven Image StylizationCode1
DiffPortrait3D: Controllable Diffusion for Zero-Shot Portrait View SynthesisCode1
DiffPO: A causal diffusion model for learning distributions of potential outcomesCode1
DiffProsody: Diffusion-based Latent Prosody Generation for Expressive Speech Synthesis with Prosody Conditional Adversarial TrainingCode1
DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain PackingCode1
DiffO: Single-step Diffusion for Image Compression at Ultra-Low BitratesCode1
DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging LoadCode1
DiffQRCoder: Diffusion-based Aesthetic QR Code Generation with Scanning Robustness Guided Iterative RefinementCode1
Diffusion Model for Dense MatchingCode1
Assessment of Data Consistency through Cascades of Independently Recurrent Inference Machines for fast and robust accelerated MRI reconstructionCode1
Empowering Diffusion Models on the Embedding Space for Text GenerationCode1
Diff-UNet: A Diffusion Embedded Network for Volumetric SegmentationCode1
Diff-IP2D: Diffusion-Based Hand-Object Interaction Prediction on Egocentric VideosCode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
DiffFashion: Reference-based Fashion Design with Structure-aware Transfer by Diffusion ModelsCode1
DifFIQA: Face Image Quality Assessment Using Denoising Diffusion Probabilistic ModelsCode1
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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