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 376–400 of 7282 papers

TitleStatusHype
MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image RestorationCode2
CustomCrafter: Customized Video Generation with Preserving Motion and Concept Composition AbilitiesCode2
Medical Vision Generalist: Unifying Medical Imaging Tasks in ContextCode2
Minutes to Seconds: Speeded-up DDPM-based Image Inpainting with Coarse-to-Fine SamplingCode2
Mixed Diffusion for 3D Indoor Scene SynthesisCode2
DiffusionBERT: Improving Generative Masked Language Models with Diffusion ModelsCode2
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly DetectionCode2
Anomaly Detection with Conditioned Denoising Diffusion ModelsCode2
Diffusion-based Generation, Optimization, and Planning in 3D ScenesCode2
Mustango: Toward Controllable Text-to-Music GenerationCode2
Diffusion Bridge Implicit ModelsCode2
AnoDDPM: Anomaly Detection With Denoising Diffusion Probabilistic Models Using Simplex NoiseCode2
Diffusion^2: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion ModelsCode2
DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image SegmentationCode2
D-AR: Diffusion via Autoregressive ModelsCode2
DiffTalk: Crafting Diffusion Models for Generalized Audio-Driven Portraits AnimationCode2
Diffusion360: Seamless 360 Degree Panoramic Image Generation based on Diffusion ModelsCode2
DiffusionDepth: Diffusion Denoising Approach for Monocular Depth EstimationCode2
DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration ModelsCode2
A DeNoising FPN With Transformer R-CNN for Tiny Object DetectionCode2
On the Generalization of BasicVSR++ to Video Deblurring and DenoisingCode2
DiffIR: Efficient Diffusion Model for Image RestorationCode2
An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion ModelsCode2
An Edit Friendly DDPM Noise Space: Inversion and ManipulationsCode2
DiffGraph: Heterogeneous Graph Diffusion ModelCode2
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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