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 301310 of 7282 papers

TitleStatusHype
Deconstructing Denoising Diffusion Models for Self-Supervised LearningCode2
Graph Diffusion Transformers for Multi-Conditional Molecular GenerationCode2
Large Language Models are Efficient Learners of Noise-Robust Speech RecognitionCode2
Fixed Point Diffusion ModelsCode2
Motion2VecSets: 4D Latent Vector Set Diffusion for Non-rigid Shape Reconstruction and TrackingCode2
Attack-Resilient Image Watermarking Using Stable DiffusionCode2
DiffLoc: Diffusion Model for Outdoor LiDAR LocalizationCode2
Exposure Bracketing Is All You Need For A High-Quality ImageCode2
FlowDiffuser: Advancing Optical Flow Estimation with Diffusion ModelsCode2
Real-World Mobile Image Denoising Dataset with Efficient BaselinesCode2
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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