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 6701–6750 of 7282 papers

TitleStatusHype
AI Generated Signal for Wireless Sensing—0
3D Point Cloud Denoising via Deep Neural Network based Local Surface Estimation—0
DRACO: A Denoising-Reconstruction Autoencoder for Cryo-EM—0
Drag-A-Video: Non-rigid Video Editing with Point-based Interaction—0
DRAG: Director-Generator Language Modelling Framework for Non-Parallel Author Stylized Rewriting—0
Drag-guided diffusion models for vehicle image generation—0
AI-Driven Segmentation and Analysis of Microbial Cells—0
DR-BFR: Degradation Representation with Diffusion Models for Blind Face Restoration—0
AI-Driven HSI: Multimodality, Fusion, Challenges, and the Deep Learning Revolution—0
A-IDE : Agent-Integrated Denoising Experts—0
Learning to adapt unknown noise for hyperspectral image denoising—0
DreamSalon: A Staged Diffusion Framework for Preserving Identity-Context in Editable Face Generation—0
A Hybrid Precipitation Prediction Method based on Multicellular Gene Expression Programming—0
DREMnet: An Interpretable Denoising Framework for Semi-Airborne Transient Electromagnetic Signal—0
DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving—0
DriveScape: High-Resolution Driving Video Generation by Multi-View Feature Fusion—0
DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning—0
An Investigation of End-to-End Multichannel Speech Recognition for Reverberant and Mismatch Conditions—0
DS2TA: Denoising Spiking Transformer with Attenuated Spatiotemporal Attention—0
DSAL-GAN: Denoising based Saliency Prediction with Generative Adversarial Networks—0
Sub-graph Based Diffusion Model for Link Prediction—0
DSplats: 3D Generation by Denoising Splats-Based Multiview Diffusion Models—0
Dual3D: Efficient and Consistent Text-to-3D Generation with Dual-mode Multi-view Latent Diffusion—0
DualBind: A Dual-Loss Framework for Protein-Ligand Binding Affinity Prediction—0
Contrastive Blind Denoising Autoencoder for Real-Time Denoising of Industrial IoT Sensor Data—0
Dual-Camera Joint Deblurring-Denoising—0
Subspace Hybrid Beamforming for Head-worn Microphone Arrays—0
Subspace modeling for fast and high-sensitivity X-ray chemical imaging—0
Dual Diffusion Architecture for Fisheye Image Rectification: Synthetic-to-Real Generalization—0
Subsurface defect imaging in PZT ceramics using dual point contact excitation and detection—0
A hybrid neuro--wavelet predictor for QoS control and stability—0
SubZero: Composing Subject, Style, and Action via Zero-Shot Personalization—0
Dual-domain Collaborative Denoising for Social Recommendation—0
A hybrid approach to seismic deblending: when physics meets self-supervision—0
DualNeRF: Text-Driven 3D Scene Editing via Dual-Field Representation—0
Dual Prompting for Diverse Count-level PET Denoising—0
DualReal: Adaptive Joint Training for Lossless Identity-Motion Fusion in Video Customization—0
Dual reparametrized Variational Generative Model for Time-Series Forecasting—0
SUD^2: Supervision by Denoising Diffusion Models for Image Reconstruction—0
Supervision by Denoising for Medical Image Segmentation—0
DuInNet: Dual-Modality Feature Interaction for Point Cloud Completion—0
DurIAN-E: Duration Informed Attention Network For Expressive Text-to-Speech Synthesis—0
DU-VLG: Unifying Vision-and-Language Generation via Dual Sequence-to-Sequence Pre-training—0
SUMD: Super U-shaped Matrix Decomposition Convolutional neural network for Image denoising—0
Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration—0
3D Point Cloud Denoising via Bipartite Graph Approximation and Reweighted Graph Laplacian—0
Dynamic Dual-Output Diffusion Models—0
Dynamic Low-light Imaging with Quanta Image Sensors—0
Dynamic Low-light Imaging with Quanta Image Sensors—0
Dynamic Point Cloud Denoising via Gradient Fields—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