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 5626–5650 of 7282 papers

TitleStatusHype
CARP: Visuomotor Policy Learning via Coarse-to-Fine Autoregressive Prediction—0
Cartoondiff: Training-free Cartoon Image Generation with Diffusion Transformer Models—0
Cascaded Convolutional Neural Networks with Perceptual Loss for Low Dose CT Denoising—0
A Novel DDPM-based Ensemble Approach for Energy Theft Detection in Smart Grids—0
Cascades of Regression Tree Fields for Image Restoration—0
Cascading Denoising Auto-Encoder as a Deep Directed Generative Model—0
Slice3D: Multi-Slice, Occlusion-Revealing, Single View 3D Reconstruction—0
Slice3D: Multi-Slice Occlusion-Revealing Single View 3D Reconstruction—0
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method—0
CDGraph: Dual Conditional Social Graph Synthesizing via Diffusion Model—0
Slice Sampling Particle Belief Propagation—0
CDPMSR: Conditional Diffusion Probabilistic Models for Single Image Super-Resolution—0
CDSA: Conservative Denoising Score-based Algorithm for Offline Reinforcement Learning—0
Test-time Adaptation in the Dynamic World with Compound Domain Knowledge Management—0
SLS (Single _1 Selection): a new greedy algorithm with an _1-norm selection rule—0
SMDS-Net: Model Guided Spectral-Spatial Network for Hyperspectral Image Denoising—0
SmoothSinger: A Conditional Diffusion Model for Singing Voice Synthesis with Multi-Resolution Architecture—0
CFA Bayer image sequence denoising and demosaicking chain—0
CFNet: Conditional Filter Learning with Dynamic Noise Estimation for Real Image Denoising—0
An Effective Image Restorer: Denoising and Luminance Adjustment for Low-photon-count Imaging—0
Chaining Identity Mapping Modules for Image Denoising—0
Chains of Autoreplicative Random Forests for missing value imputation in high-dimensional datasets—0
ChaLearn Looking at People: Inpainting and Denoising challenges—0
Change Detection from Synthetic Aperture Radar Images via Dual Path Denoising Network—0
Channel-adaptive Cross-modal Generative Semantic Communication for Point Cloud Transmission—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