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 2101–2150 of 7282 papers

TitleStatusHype
Classic Video Denoising in a Machine Learning World: Robust, Fast, and Controllable—0
VIP: Video Inpainting Pipeline for Real World Human Removal—0
Analytical Discovery of Manifold with Machine Learning—0
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance—0
Enhancing LLM Robustness to Perturbed Instructions: An Empirical StudyCode0
MD-ProjTex: Texturing 3D Shapes with Multi-Diffusion Projection—0
Foreground Focus: Enhancing Coherence and Fidelity in Camouflaged Image Generation—0
Bridge the Gap between SNN and ANN for Image Restoration—0
BioAtt: Anatomical Prior Driven Low-Dose CT Denoising—0
Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-TrainingCode0
A Unified Approach to Analysis and Design of Denoising Markov Models—0
Random Conditioning with Distillation for Data-Efficient Diffusion Model Compression—0
VideoScene: Distilling Video Diffusion Model to Generate 3D Scenes in One Step—0
Denoising guarantees for optimized sampling schemes in compressed sensing—0
Deep Learning-Based Extended Target Tracking in ISAC Systems—0
OccludeNeRF: Geometric-aware 3D Scene Inpainting with Collaborative Score Distillation in NeRF—0
MixerMDM: Learnable Composition of Human Motion Diffusion Models—0
DiffDenoise: Self-Supervised Medical Image Denoising with Conditional Diffusion Models—0
ExScene: Free-View 3D Scene Reconstruction with Gaussian Splatting from a Single Image—0
DenseFormer: Learning Dense Depth Map from Sparse Depth and Image via Conditional Diffusion Model—0
Enhancing Image Resolution of Solar Magnetograms: A Latent Diffusion Model ApproachCode0
SU-YOLO: Spiking Neural Network for Efficient Underwater Object DetectionCode0
Foundation Models For Seismic Data Processing: An Extensive ReviewCode0
Make Autoregressive Great Again: Diffusion-Free Graph Generation with Next-Scale Prediction—0
RuleAgent: Discovering Rules for Recommendation Denoising with Autonomous Language Agents—0
TRACE: Intra-visit Clinical Event Nowcasting via Effective Patient Trajectory EncodingCode0
Score-Based Turbo Message Passing for Plug-and-Play Compressive Image Recovery—0
DREMnet: An Interpretable Denoising Framework for Semi-Airborne Transient Electromagnetic Signal—0
Patronus: Bringing Transparency to Diffusion Models with PrototypesCode0
GCRayDiffusion: Pose-Free Surface Reconstruction via Geometric Consistent Ray Diffusion—0
Spatial Transport Optimization by Repositioning Attention Map for Training-Free Text-to-Image Synthesis—0
RELD: Regularization by Latent Diffusion Models for Image Restoration—0
Interpretable Deep Learning Paradigm for Airborne Transient Electromagnetic Inversion—0
HORT: Monocular Hand-held Objects Reconstruction with Transformers—0
Unsupervised Real-World Denoising: Sparsity is All You Need—0
DeCompress: Denoising via Neural Compression—0
HybridoNet-Adapt: A Domain-Adapted Framework for Accurate Lithium-Ion Battery RUL Prediction—0
Diffusion Image Prior—0
AGILE: A Diffusion-Based Attention-Guided Image and Label Translation for Efficient Cross-Domain Plant Trait IdentificationCode0
Critical Iterative Denoising: A Discrete Generative Model Applied to Graphs—0
ITA-MDT: Image-Timestep-Adaptive Masked Diffusion Transformer Framework for Image-Based Virtual Try-On—0
Exploring Robustness of Cortical Morphometry in the presence of white matter lesions, using Diffusion Models for Lesion Filling—0
MAR-3D: Progressive Masked Auto-regressor for High-Resolution 3D Generation—0
Traversing Distortion-Perception Tradeoff using a Single Score-Based Generative Model—0
Zero-Shot Audio-Visual Editing via Cross-Modal Delta Denoising—0
Implicit neural representations for end-to-end PET reconstruction—0
Diffusion Counterfactuals for Image RegressorsCode0
Towards Robust Time-of-Flight Depth Denoising with Confidence-Aware Diffusion Model—0
PCM : Picard Consistency Model for Fast Parallel Sampling of Diffusion Models—0
BADGR: Bundle Adjustment Diffusion Conditioned by GRadients for Wide-Baseline Floor Plan Reconstruction—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