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 1201–1225 of 7282 papers

TitleStatusHype
Neighboring Slice Noise2Noise: Self-Supervised Medical Image Denoising from Single Noisy Image Volume—0
Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolution—0
MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious CorrelationsCode0
DR-BFR: Degradation Representation with Diffusion Models for Blind Face Restoration—0
Imagine-2-Drive: Leveraging High-Fidelity World Models via Multi-Modal Diffusion Policies—0
ColorEdit: Training-free Image-Guided Color editing with diffusion model—0
Learning Generalizable 3D Manipulation With 10 DemonstrationsCode0
Probabilistic Prior Driven Attention Mechanism Based on Diffusion Model for Imaging Through Atmospheric Turbulence—0
Enhancing Diffusion Posterior Sampling for Inverse Problems by Integrating Crafted Measurements—0
VidMan: Exploiting Implicit Dynamics from Video Diffusion Model for Effective Robot Manipulation—0
Video Denoising in Fluorescence Guided Surgery—0
Graph Neural Networks and Differential Equations: A hybrid approach for data assimilation of fluid flows—0
A survey of probabilistic generative frameworks for molecular simulationsCode0
Iterative tomographic reconstruction with TV prior for low-dose CBCT dental imaging—0
EEG-Based Speech Decoding: A Novel Approach Using Multi-Kernel Ensemble Diffusion Models—0
DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation—0
GAN-Based Architecture for Low-dose Computed Tomography Imaging Denoising—0
DiffRoad: Realistic and Diverse Road Scenario Generation for Autonomous Vehicle Testing—0
Confidence-aware Denoised Fine-tuning of Off-the-shelf Models for Certified RobustnessCode0
DNN Task Assignment in UAV Networks: A Generative AI Enhanced Multi-Agent Reinforcement Learning Approach—0
V2X-R: Cooperative LiDAR-4D Radar Fusion for 3D Object Detection with Denoising DiffusionCode2
Explainable Deep Learning Framework for SERS Bio-quantification—0
CT-Mamba: A Hybrid Convolutional State Space Model for Low-Dose CT DenoisingCode1
ALOcc: Adaptive Lifting-based 3D Semantic Occupancy and Cost Volume-based Flow PredictionCode1
Joint multi-dimensional dynamic attention and transformer for general image restorationCode1
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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