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

Showing 326350 of 7282 papers

TitleStatusHype
Anomaly Detection with Conditioned Denoising Diffusion ModelsCode2
Diffusion Bridge Implicit ModelsCode2
GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising DiffusionCode2
Diffusion-based Generation, Optimization, and Planning in 3D ScenesCode2
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly DetectionCode2
Generative Diffusion Models on Graphs: Methods and ApplicationsCode2
Generative Time Series Forecasting with Diffusion, Denoise, and DisentanglementCode2
CascadedGaze: Efficiency in Global Context Extraction for Image RestorationCode2
CARD: Classification and Regression Diffusion ModelsCode2
Diffusion-based Visual Anagram as Multi-task LearningCode2
CGVQM+D: Computer Graphics Video Quality Metric and DatasetCode2
DiffusionDepth: Diffusion Denoising Approach for Monocular Depth EstimationCode2
DiffusionInst: Diffusion Model for Instance SegmentationCode2
Diffusion Transformer PolicyCode2
High-Precision Dichotomous Image Segmentation via Probing Diffusion CapacityCode2
DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image SegmentationCode2
DiffTalk: Crafting Diffusion Models for Generalized Audio-Driven Portraits AnimationCode2
DiffiT: Diffusion Vision Transformers for Image GenerationCode2
HumanMAC: Masked Motion Completion for Human Motion PredictionCode2
HumanSD: A Native Skeleton-Guided Diffusion Model for Human Image GenerationCode2
Hybrid Convolutional and Attention Network for Hyperspectral Image DenoisingCode2
CM-TTS: Enhancing Real Time Text-to-Speech Synthesis Efficiency through Weighted Samplers and Consistency ModelsCode2
CMGAN: Conformer-Based Metric-GAN for Monaural Speech EnhancementCode2
An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion ModelsCode2
DiffLoc: Diffusion Model for Outdoor LiDAR LocalizationCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified