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 21512160 of 7282 papers

TitleStatusHype
Inference-Time Scaling for Flow Models via Stochastic Generation and Rollover Budget Forcing0
Towards Robust Time-of-Flight Depth Denoising with Confidence-Aware Diffusion Model0
Discriminative protein sequence modelling with Latent Space Diffusion0
Hiding Images in Diffusion Models by Editing Learned Score FunctionsCode0
Video-T1: Test-Time Scaling for Video Generation0
HunyuanPortrait: Implicit Condition Control for Enhanced Portrait Animation0
Training-free Diffusion Acceleration with Bottleneck Sampling0
AIM2PC: Aerial Image to 3D Building Point Cloud ReconstructionCode0
Dig2DIG: Dig into Diffusion Information Gains for Image Fusion0
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos0
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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