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 4626–4650 of 7282 papers

TitleStatusHype
Processing stationary noise: model and parameter selection in variational methods—0
A Coupling Enhancement Algorithm for ZrO2 Ceramic Bearing Ball Surface Defect Detection Based on Cartoon-texture Decomposition Model and Multi-Scale Filtering Method—0
PRoDeliberation: Parallel Robust Deliberation for End-to-End Spoken Language Understanding—0
A Coordinate Descent Approach to Atomic Norm Denoising—0
WhiteNNer-Blind Image Denoising via Noise Whiteness Priors—0
Product-Level Try-on: Characteristics-preserving Try-on with Realistic Clothes Shading and Wrinkles—0
ProFashion: Prototype-guided Fashion Video Generation with Multiple Reference Images—0
Programmable Annotation with Diversed Heuristics and Data Denoising—0
A Convex Functional for Image Denoising based on Patches with Constrained Overlaps and its vectorial application to Low Dose Differential Phase Tomography—0
Progressive Text-to-Image Generation—0
Unified Noise-aware Network for Low-count PET Denoising—0
ProgressiveMotionSeg: Mutually Reinforced Framework for Event-Based Motion Segmentation—0
Whole-body PET image denoising for reduced acquisition time—0
Unified Representation Learning for Efficient Medical Image Analysis—0
Project Achoo: A Practical Model and Application for COVID-19 Detection from Recordings of Breath, Voice, and Cough—0
Projection-Free Algorithm for Stochastic Bi-level Optimization—0
Promoting Graph Awareness in Linearized Graph-to-Text Generation—0
PromptBERT: Improving BERT Sentence Embeddings with Prompts—0
A Constrained Optimization approach for Ultrasound Shear Wave Speed Estimation with Time-Lateral Plane Cleaning—0
Unified Uncertainty-Aware Diffusion for Multi-Agent Trajectory Modeling—0
A Computationally Efficient Method for Defending Adversarial Deep Learning Attacks—0
UniFlowRestore: A General Video Restoration Framework via Flow Matching and Prompt Guidance—0
Propagated Image Filtering—0
Properties of Laplacian Pyramids for Extension and Denoising—0
Properties on n-dimensional convolution for image deconvolution—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