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 1701–1725 of 7282 papers

TitleStatusHype
You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph LearningCode0
DNTextSpotter: Arbitrary-Shaped Scene Text Spotting via Improved Denoising TrainingCode1
Advancing Medical Image Segmentation: Morphology-Driven Learning with Diffusion TransformerCode0
SegStitch: Multidimensional Transformer for Robust and Efficient Medical Imaging SegmentationCode0
Temporal Evolution of Knee Osteoarthritis: A Diffusion-based Morphing Model for X-ray Medical Image Synthesis—0
Learned Single-Pass Multitasking Perceptual Graphics for Immersive Displays—0
CL-DiffPhyCon: Closed-loop Diffusion Control of Complex Physical SystemsCode1
On the Perturbed States for Transformed Input-robust Reinforcement LearningCode0
Robust Simultaneous Multislice MRI Reconstruction Using Deep Generative PriorsCode0
A Constrained Optimization approach for Ultrasound Shear Wave Speed Estimation with Time-Lateral Plane Cleaning—0
Robust CNN Multi-Nested-LSTM Framework with Compound Loss for Patch-based Multi-Push Ultrasound Shear Wave Imaging and Segmentation—0
HandDAGT: A Denoising Adaptive Graph Transformer for 3D Hand Pose EstimationCode0
Restoring Real-World Degraded Events Improves Deblurring QualityCode0
Deep Image Priors for Magnetic Resonance Fingerprinting with pretrained Bloch-consistent denoising autoencoders—0
Denoising ESG: quantifying data uncertainty from missing data with Machine Learning and prediction intervals—0
Specify and Edit: Overcoming Ambiguity in Text-Based Image EditingCode0
FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention—0
Map2Traj: Street Map Piloted Zero-shot Trajectory Generation with Diffusion Model—0
Interpreting Low-level Vision Models with Causal Effect MapsCode1
Pixel-Level GPS Localization and Denoising using Computer Vision and 6G Communication Beams—0
FIND: Fine-tuning Initial Noise Distribution with Policy Optimization for Diffusion ModelsCode0
Cycle3D: High-quality and Consistent Image-to-3D Generation via Generation-Reconstruction Cycle—0
White Matter Geometry-Guided Score-Based Diffusion Model for Tissue Microstructure Imputation in Tractography ImagingCode0
Temporal Feature Matters: A Framework for Diffusion Model QuantizationCode2
Learning to Enhance Aperture Phasor Field for Non-Line-of-Sight ImagingCode1
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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