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 521530 of 7282 papers

TitleStatusHype
Content-Noise Complementary Learning for Medical Image DenoisingCode1
Diffusion Model as Representation LearnerCode1
Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned GenerationCode1
CL-DiffPhyCon: Closed-loop Diffusion Control of Complex Physical SystemsCode1
Controlling Latent Diffusion Using Latent CLIPCode1
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be ConsistentCode1
ConsistencyTTA: Accelerating Diffusion-Based Text-to-Audio Generation with Consistency DistillationCode1
Continual Learning of Diffusion Models with Generative DistillationCode1
Diffusion Model Based Posterior Sampling for Noisy Linear Inverse ProblemsCode1
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain ImagesCode1
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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