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 3301–3310 of 7282 papers

TitleStatusHype
ManiCM: Real-time 3D Diffusion Policy via Consistency Model for Robotic Manipulation—0
Convergence of the denoising diffusion probabilistic models for general noise schedules—0
Advancing Weakly-Supervised Audio-Visual Video Parsing via Segment-wise Pseudo Labeling—0
Diffusion Boosted Trees—0
Imitating the Functionality of Image-to-Image Models Using a Single Example—0
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting—0
Bootstrap3D: Improving Multi-view Diffusion Model with Synthetic Data—0
Unified Directly Denoising for Both Variance Preserving and Variance Exploding Diffusion Models—0
Information Maximization via Variational Autoencoders for Cross-Domain Recommendation—0
Knowledge Enhanced Multi-intent Transformer Network for RecommendationCode0
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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