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 451–460 of 7282 papers

TitleStatusHype
MD-ProjTex: Texturing 3D Shapes with Multi-Diffusion Projection—0
Foreground Focus: Enhancing Coherence and Fidelity in Camouflaged Image Generation—0
Random Conditioning with Distillation for Data-Efficient Diffusion Model Compression—0
BioAtt: Anatomical Prior Driven Low-Dose CT Denoising—0
Bridge the Gap between SNN and ANN for Image Restoration—0
VideoScene: Distilling Video Diffusion Model to Generate 3D Scenes in One Step—0
A Unified Approach to Analysis and Design of Denoising Markov Models—0
Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-TrainingCode0
MixerMDM: Learnable Composition of Human Motion Diffusion Models—0
OccludeNeRF: Geometric-aware 3D Scene Inpainting with Collaborative Score Distillation in NeRF—0
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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