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 231240 of 7282 papers

TitleStatusHype
FRAG: Frequency Adapting Group for Diffusion Video EditingCode2
ProcessPainter: Learn Painting Process from Sequence DataCode2
A DeNoising FPN With Transformer R-CNN for Tiny Object DetectionCode2
Medical Vision Generalist: Unifying Medical Imaging Tasks in ContextCode2
Streaming Diffusion Policy: Fast Policy Synthesis with Variable Noise Diffusion ModelsCode2
Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean DataCode2
SF-V: Single Forward Video Generation ModelCode2
Ouroboros3D: Image-to-3D Generation via 3D-aware Recursive DiffusionCode2
Learning-to-Cache: Accelerating Diffusion Transformer via Layer CachingCode2
RecDiff: Diffusion Model for Social RecommendationCode2
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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