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 3011–3020 of 7282 papers

TitleStatusHype
Convolutional Neural Networks Analyzed via Inverse Problem Theory and Sparse Representations—0
Gradient-free Decoder Inversion in Latent Diffusion Models—0
FrePolad: Frequency-Rectified Point Latent Diffusion for Point Cloud Generation—0
Frequency-Aware Guidance for Blind Image Restoration via Diffusion Models—0
A Face Fairness Framework for 3D Meshes—0
Frequency Domain Loss Function for Deep Exposure Correction of Dark Images—0
Evaluating the design space of diffusion-based generative models—0
Frequency-Time Diffusion with Neural Cellular Automata—0
Frequency-Weighted Robust Tensor Principal Component Analysis—0
4D X-Ray CT Reconstruction using Multi-Slice Fusion—0
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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