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 531540 of 7282 papers

TitleStatusHype
SceneMI: Motion In-betweening for Modeling Human-Scene Interactions0
Scale-wise Distillation of Diffusion Models0
Temporal Score Analysis for Understanding and Correcting Diffusion Artifacts0
BlockDance: Reuse Structurally Similar Spatio-Temporal Features to Accelerate Diffusion Transformers0
MiLA: Multi-view Intensive-fidelity Long-term Video Generation World Model for Autonomous DrivingCode1
DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup TablesCode2
Denoising-based Contractive Imitation LearningCode0
Shining Yourself: High-Fidelity Ornaments Virtual Try-on with Diffusion Model0
ScalingNoise: Scaling Inference-Time Search for Generating Infinite Videos0
Patch-based learning of adaptive Total Variation parameter maps for blind image denoising0
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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