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 10211030 of 7282 papers

TitleStatusHype
Diffusion Model from Scratch0
Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-ReflectionCode2
SoftVQ-VAE: Efficient 1-Dimensional Continuous TokenizerCode3
SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device0
FM2S: Towards Spatially-Correlated Noise Modeling in Zero-Shot Fluorescence Microscopy Image DenoisingCode1
Dynamic Try-On: Taming Video Virtual Try-on with Dynamic Attention Mechanism0
SuperMark: Robust and Training-free Image Watermarking via Diffusion-based Super-Resolution0
FaceShield: Defending Facial Image against Deepfake Threats0
EP-CFG: Energy-Preserving Classifier-Free Guidance0
Self-Consistent Nested Diffusion Bridge for Accelerated MRI Reconstruction0
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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