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 2726–2750 of 7282 papers

TitleStatusHype
FreeInit: Bridging Initialization Gap in Video Diffusion ModelsCode2
Fast Training of Diffusion Transformer with Extreme Masking for 3D Point Clouds Generation—0
Generating High-Resolution Regional Precipitation Using Conditional Diffusion Model—0
DiffuVST: Narrating Fictional Scenes with Global-History-Guided Denoising Models—0
Learning to See Low-Light Images via Feature Domain Adaptation—0
Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance ScaleCode1
Robust Graph Neural Network based on Graph DenoisingCode0
DiAD: A Diffusion-based Framework for Multi-class Anomaly DetectionCode2
The Journey, Not the Destination: How Data Guides Diffusion ModelsCode1
PCRDiffusion: Diffusion Probabilistic Models for Point Cloud Registration—0
CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy LabelsCode1
Textual Prompt Guided Image RestorationCode1
Optimized View and Geometry Distillation from Multi-view DiffuserCode1
MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion AttacksCode1
VisionTraj: A Noise-Robust Trajectory Recovery Framework based on Large-scale Camera NetworkCode0
Compensation Sampling for Improved Convergence in Diffusion ModelsCode0
DiT-Head: High-Resolution Talking Head Synthesis using Diffusion Transformers—0
Class-Prototype Conditional Diffusion Model with Gradient Projection for Continual Learning—0
A Note on the Convergence of Denoising Diffusion Probabilistic Models—0
Learning to Denoise Biomedical Knowledge Graph for Robust Molecular Interaction PredictionCode0
DPoser: Diffusion Model as Robust 3D Human Pose PriorCode2
D3A-TS: Denoising-Driven Data Augmentation in Time SeriesCode1
Consistency Models for Scalable and Fast Simulation-Based InferenceCode0
A global optimization SAR image segmentation model can be easily transformed to a general ROF denoising model—0
Uncertainty-aware Surrogate Models for Airfoil Flow Simulations with Denoising Diffusion Probabilistic ModelsCode1
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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