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 23912400 of 7282 papers

TitleStatusHype
Listening to the Noise: Blind Denoising with Gibbs DiffusionCode1
Graph Generation via Spectral Diffusion0
Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-DecodingCode0
CollaFuse: Navigating Limited Resources and Privacy in Collaborative Generative AICode0
ViewFusion: Towards Multi-View Consistency via Interpolated DenoisingCode2
Balancing Act: Distribution-Guided Debiasing in Diffusion Models0
ROG_PL: Robust Open-Set Graph Learning via Region-Based Prototype Learning0
Multi-Scale Denoising in the Feature Space for Low-Light Instance Segmentation0
Self-Supervised Learning with Generative Adversarial Networks for Electron Microscopy0
Objective and Interpretable Breast Cosmesis Evaluation with Attention Guided Denoising Diffusion Anomaly Detection Model0
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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