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 441450 of 7282 papers

TitleStatusHype
FaR: Enhancing Multi-Concept Text-to-Image Diffusion via Concept Fusion and Localized Refinement0
DP-LET: An Efficient Spatio-Temporal Network Traffic Prediction Framework0
TQD-Track: Temporal Query Denoising for 3D Multi-Object Tracking0
Dynamic Importance in Diffusion U-Net for Enhanced Image SynthesisCode0
Model Reveals What to Cache: Profiling-Based Feature Reuse for Video Diffusion ModelsCode1
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance0
VIP: Video Inpainting Pipeline for Real World Human Removal0
Fine-Tuning Visual Autoregressive Models for Subject-Driven GenerationCode1
Analytical Discovery of Manifold with Machine Learning0
Enhancing LLM Robustness to Perturbed Instructions: An Empirical StudyCode0
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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