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 3901–3925 of 7282 papers

TitleStatusHype
Frequency-Weighted Robust Tensor Principal Component Analysis—0
Dynamic Point Cloud Denoising via Manifold-to-Manifold Distance—0
FRIST - Flipping and Rotation Invariant Sparsifying Transform Learning and Applications—0
FRMD: Fast Robot Motion Diffusion with Consistency-Distilled Movement Primitives for Smooth Action Generation—0
From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging—0
From Data to Action: Charting A Data-Driven Path to Combat Antimicrobial Resistance—0
Zero-Shot Audio-Visual Editing via Cross-Modal Delta Denoising—0
From Score Matching to Diffusion: A Fine-Grained Error Analysis in the Gaussian Setting—0
Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back—0
TaQ-DiT: Time-aware Quantization for Diffusion Transformers—0
From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration—0
From Incomplete Coarse-Grained to Complete Fine-Grained: A Two-Stage Framework for Spatiotemporal Data Reconstruction—0
From Noise Modeling to Blind Image Denoising—0
Temporal Evolution of Knee Osteoarthritis: A Diffusion-based Morphing Model for X-ray Medical Image Synthesis—0
From Real Artifacts to Virtual Reference: A Robust Framework for Translating Endoscopic Images—0
From Simulated to Visual Data: A Robust Low-Rank Tensor Completion Approach using lp-Regression for Outlier Resistance—0
From thermodynamics to protein design: Diffusion models for biomolecule generation towards autonomous protein engineering—0
Frustratingly Simple Prompting-based Text Denoising—0
AE-RED: A Hyperspectral Unmixing Framework Powered by Deep Autoencoder and Regularization by Denoising—0
Targeted Adversarial Denoising Autoencoders (TADA) for Neural Time Series Filtration—0
Full-reference Point Cloud Quality Assessment Using Spectral Graph Wavelets—0
Fully-Connected CRFs with Non-Parametric Pairwise Potential—0
Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning—0
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series—0
Target Score Matching—0
Show:102550
← PrevPage 157 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