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 201–250 of 7282 papers

TitleStatusHype
Improved Immiscible Diffusion: Accelerate Diffusion Training by Reducing Its MiscibilityCode2
Restoring Real-World Images with an Internal Detail Enhancement Diffusion Model—0
On Denoising Walking Videos for Gait RecognitionCode0
CIM-NET: A Video Denoising Deep Neural Network Model Optimized for Computing-in-Memory Architectures—0
RestoreVAR: Visual Autoregressive Generation for All-in-One Image Restoration—0
Towards more transferable adversarial attack in black-box manner—0
Applications of Modular Co-Design for De Novo 3D Molecule Generation—0
Brightness-Invariant Tracking Estimation in Tagged MRI—0
CONCORD: Concept-Informed Diffusion for Dataset DistillationCode0
Consistent World Models via Foresight Diffusion—0
SHaDe: Compact and Consistent Dynamic 3D Reconstruction via Tri-Plane Deformation and Latent Diffusion—0
REPA Works Until It Doesn't: Early-Stopped, Holistic Alignment Supercharges Diffusion TrainingCode1
Training-Free Efficient Video Generation via Dynamic Token CarvingCode3
TRAIL: Transferable Robust Adversarial Images via Latent diffusion—0
Joint Flow And Feature Refinement Using Attention For Video Restoration—0
OSCAR: One-Step Diffusion Codec for Image Compression Across Multiple Bit-ratesCode1
Pursuing Temporal-Consistent Video Virtual Try-On via Dynamic Pose Interaction—0
Guided Diffusion Sampling on Function Spaces with Applications to PDEsCode1
Active Speech Enhancement: Active Speech Denoising Decliping and Deveraberation—0
Sufficient conditions for offline reactivation in recurrent neural networksCode0
Creatively Upscaling Images with Global-Regional Priors—0
Image-to-Image Translation with Diffusion Transformers and CLIP-Based Image Conditioning—0
Toward Theoretical Insights into Diffusion Trajectory Distillation via Operator Merging—0
dKV-Cache: The Cache for Diffusion Language ModelsCode2
Diffusion Probabilistic Generative Models for Accelerated, in-NICU Permanent Magnet Neonatal MRI—0
Decoding Phone Pairs from MEG Signals Across Speech ModalitiesCode0
DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation TrainerCode1
Adaptive Estimation and Learning under Temporal Distribution Shift—0
Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering—0
Beyond Classification: Evaluating Diffusion Denoised Smoothing for Security-Utility Trade off—0
Non-rigid Motion Correction for MRI Reconstruction via Coarse-To-Fine Diffusion Models—0
Time Series Similarity Score Functions to Monitor and Interact with the Training and Denoising Process of a Time Series Diffusion Model applied to a Human Activity Recognition Dataset based on IMUs—0
Multi-Channel Swin Transformer Framework for Bearing Remaining Useful Life Prediction—0
Communication-Efficient Diffusion Denoising Parallelization via Reuse-then-Predict Mechanism—0
RefiDiff: Refinement-Aware Diffusion for Efficient Missing Data Imputation—0
Adaptive Cyclic Diffusion for Inference Scaling—0
Neural Inverse Scattering with Score-based Regularization—0
AquaSignal: An Integrated Framework for Robust Underwater Acoustic AnalysisCode0
Improving Noise Robustness of LLM-based Zero-shot TTS via Discrete Acoustic Token Denoising—0
Stochastic Orthogonal Regularization for deep projective priors—0
Higher fidelity perceptual image and video compression with a latent conditioned residual denoising diffusion modelCode0
AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool UseCode1
Restoration Score Distillation: From Corrupted Diffusion Pretraining to One-Step High-Quality Generation—0
Degradation-Aware Feature Perturbation for All-in-One Image RestorationCode2
FlowPure: Continuous Normalizing Flows for Adversarial PurificationCode1
RoPECraft: Training-Free Motion Transfer with Trajectory-Guided RoPE Optimization on Diffusion Transformers—0
Anti-Inpainting: A Proactive Defense against Malicious Diffusion-based Inpainters under Unknown Conditions—0
Denoising Diffusion Probabilistic Model for Point Cloud Compression at Low Bit-RatesCode0
Addressing Missing Data Issue for Diffusion-based RecommendationCode0
CTLformer: A Hybrid Denoising Model Combining Convolutional Layers and Self-Attention for Enhanced CT Image 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