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 28412850 of 7282 papers

TitleStatusHype
Using Human Feedback to Fine-tune Diffusion Models without Any Reward ModelCode2
FrePolad: Frequency-Rectified Point Latent Diffusion for Point Cloud Generation0
Mixing-Denoising Generalizable Occupancy Networks0
Gaussian Interpolation Flows0
Sparse4D v3: Advancing End-to-End 3D Detection and TrackingCode2
An Image is Worth Multiple Words: Multi-attribute Inversion for Constrained Text-to-Image Synthesis0
GaussianDiffusion: 3D Gaussian Splatting for Denoising Diffusion Probabilistic Models with Structured Noise0
DiffSCI: Zero-Shot Snapshot Compressive Imaging via Iterative Spectral Diffusion ModelCode0
SDDPM: Speckle Denoising Diffusion Probabilistic Models0
FedDiff: Diffusion Model Driven Federated Learning for Multi-Modal and Multi-Clients0
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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