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 2831–2840 of 7282 papers

TitleStatusHype
Truncated Consistency Models—0
Unified Convergence Analysis for Score-Based Diffusion Models with Deterministic Samplers—0
SGD Jittering: A Training Strategy for Robust and Accurate Model-Based Architectures—0
RA-BLIP: Multimodal Adaptive Retrieval-Augmented Bootstrapping Language-Image Pre-training—0
Heavy-Tailed Diffusion Models—0
Dynamic Negative Guidance of Diffusion ModelsCode0
Multi-modal Pose Diffuser: A Multimodal Generative Conditional Pose Prior—0
DiffImp: Efficient Diffusion Model for Probabilistic Time Series Imputation with Bidirectional Mamba Backbone—0
Meta-DiffuB: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-ExplorationCode0
Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers—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