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 1001–1050 of 7282 papers

TitleStatusHype
Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask LearningCode2
3D MedDiffusion: A 3D Medical Diffusion Model for Controllable and High-quality Medical Image Generation—0
Machine Learning-Based Automated Assessment of Intracorporeal Suturing in Laparoscopic Fundoplication—0
Bilevel Learning with Inexact Stochastic GradientsCode0
Probabilities-Informed Machine Learning—0
Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Model—0
Re-Attentional Controllable Video Diffusion EditingCode1
3D^2-Actor: Learning Pose-Conditioned 3D-Aware Denoiser for Realistic Gaussian Avatar ModelingCode1
AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration—0
Spatiotemporal Blind-Spot Network with Calibrated Flow Alignment for Self-Supervised Video DenoisingCode1
MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes—0
SPADE: Spectroscopic Photoacoustic Denoising using an Analytical and Data-free Enhancement Framework—0
Missing data imputation for noisy time-series data and applications in healthcare—0
DynamicScaler: Seamless and Scalable Video Generation for Panoramic Scenes—0
OTLRM: Orthogonal Learning-based Low-Rank Metric for Multi-Dimensional Inverse ProblemsCode1
Fast and Robust Visuomotor Riemannian Flow Matching Policy—0
Diffusion-based Method for Satellite Pattern-of-Life Identification—0
Rapid Reconstruction of Extremely Accelerated Liver 4D MRI via Chained Iterative Refinement—0
Generative Modeling with DiffusionCode0
LAN: Learning to Adapt Noise for Image DenoisingCode1
Diffusion Model from Scratch—0
Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-ReflectionCode2
SoftVQ-VAE: Efficient 1-Dimensional Continuous TokenizerCode3
SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device—0
SuperMark: Robust and Training-free Image Watermarking via Diffusion-based Super-Resolution—0
FaceShield: Defending Facial Image against Deepfake Threats—0
Dynamic Try-On: Taming Video Virtual Try-on with Dynamic Attention Mechanism—0
FM2S: Towards Spatially-Correlated Noise Modeling in Zero-Shot Fluorescence Microscopy Image DenoisingCode1
Self-Consistent Nested Diffusion Bridge for Accelerated MRI Reconstruction—0
EP-CFG: Energy-Preserving Classifier-Free Guidance—0
Diffusion Predictive Control with ConstraintsCode2
Inference-Time Diffusion Model DistillationCode0
Reversing the Damage: A QP-Aware Transformer-Diffusion Approach for 8K Video Restoration under Codec CompressionCode1
Diffusion Model with Representation Alignment for Protein Inverse Folding—0
RealOSR: Latent Unfolding Boosting Diffusion-based Real-world Omnidirectional Image Super-ResolutionCode0
Physics Meets Pixels: PDE Models in Image Processing—0
DSplats: 3D Generation by Denoising Splats-Based Multiview Diffusion Models—0
DALI: Domain Adaptive LiDAR Object Detection via Distribution-level and Instance-level Pseudo Label DenoisingCode0
Convergence Analysis of a Proximal Stochastic Denoising Regularization Algorithm—0
Analyzing and Improving Model Collapse in Rectified Flow Models—0
GenPlan: Generative Sequence Models as Adaptive PlannersCode0
Fair Primal Dual Splitting Method for Image Inverse Problems—0
TouchTTS: An Embarrassingly Simple TTS Framework that Everyone Can Touch—0
Video Summarization using Denoising Diffusion Probabilistic Model—0
Zero-Shot Mono-to-Binaural Speech Synthesis—0
DiffRaman: A Conditional Latent Denoising Diffusion Probabilistic Model for Bacterial Raman Spectroscopy Identification Under Limited Data Conditions—0
Adversarial Contrastive Domain-Generative Learning for Bacteria Raman Spectrum Joint Denoising and Cross-Domain Identification—0
A Dual-Module Denoising Approach with Curriculum Learning for Enhancing Multimodal Aspect-Based Sentiment Analysis—0
Closed-Form Approximation of the Total Variation Proximal Operator—0
Mask prior-guided denoising diffusion improves inverse protein foldingCode1
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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