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 1426–1450 of 7282 papers

TitleStatusHype
VideoGuide: Improving Video Diffusion Models without Training Through a Teacher's Guide—0
From Incomplete Coarse-Grained to Complete Fine-Grained: A Two-Stage Framework for Spatiotemporal Data Reconstruction—0
Consistent Autoformalization for Constructing Mathematical LibrariesCode0
DeFoG: Discrete Flow Matching for Graph GenerationCode2
Epsilon-VAE: Denoising as Visual Decoding—0
Multiscale Latent Diffusion Model for Enhanced Feature Extraction from Medical Images—0
TrustEMG-Net: Using Representation-Masking Transformer with U-Net for Surface Electromyography EnhancementCode1
Learning Truncated Causal History Model for Video RestorationCode2
Structure-Enhanced Protein Instruction Tuning: Towards General-Purpose Protein Understanding with LLMs—0
Aircraft Radar Altimeter Interference Mitigation Through a CNN-Layer Only Denoising Autoencoder Architecture—0
Generative Edge Detection with Stable Diffusion—0
VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning—0
Classification-Denoising Networks—0
Minmax Trend Filtering: Generalizations of Total Variation Denoising via a Local Minmax/Maxmin Formula—0
PnP-Flow: Plug-and-Play Image Restoration with Flow MatchingCode2
MDSGen: Fast and Efficient Masked Diffusion Temporal-Aware Transformers for Open-Domain Sound Generation—0
RDEIC: Accelerating Diffusion-Based Extreme Image Compression with Relay Residual DiffusionCode1
Combining Pre- and Post-Demosaicking Noise Removal for RAW Video—0
SCA: Improve Semantic Consistent in Unrestricted Adversarial Attacks via DDPM InversionCode0
Event-Customized Image Generation—0
An Improved Variational Method for Image Denoising—0
SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric GroupsCode1
Diffusion Models are Evolutionary AlgorithmsCode3
Channel-aware Contrastive Conditional Diffusion for Multivariate Probabilistic Time Series ForecastingCode0
A Real Benchmark Swell Noise Dataset for Performing Seismic Data Denoising via Deep Learning—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