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 5175 of 7282 papers

TitleStatusHype
DiffuCoder: Understanding and Improving Masked Diffusion Models for Code GenerationCode4
One Step Diffusion via Shortcut ModelsCode4
PromptFix: You Prompt and We Fix the PhotoCode4
Multimodal-Conditioned Latent Diffusion Models for Fashion Image EditingCode3
3D Diffuser Actor: Policy Diffusion with 3D Scene RepresentationsCode3
MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse ViewsCode3
3D Diffuser Actor: Policy Diffusion with 3D Scene RepresentationsCode3
Make-Your-Anchor: A Diffusion-based 2D Avatar Generation FrameworkCode3
MAXIM: Multi-Axis MLP for Image ProcessingCode3
ModelScope Text-to-Video Technical ReportCode3
DDT: Decoupled Diffusion TransformerCode3
MotionFollower: Editing Video Motion via Lightweight Score-Guided DiffusionCode3
LinFusion: 1 GPU, 1 Minute, 16K ImageCode3
AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and ModulationCode3
Inversion-Free Image Editing with Language-Guided Diffusion ModelsCode3
3D-Adapter: Geometry-Consistent Multi-View Diffusion for High-Quality 3D GenerationCode3
Image Quality Assessment for Magnetic Resonance ImagingCode3
Improved Denoising Diffusion Probabilistic ModelsCode3
Instruct-IPT: All-in-One Image Processing Transformer via Weight ModulationCode3
HAT: Hybrid Attention Transformer for Image RestorationCode3
GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous DrivingCode3
Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force FieldsCode3
High-Resolution Image Reconstruction With Latent Diffusion Models From Human Brain ActivityCode3
Free4D: Tuning-free 4D Scene Generation with Spatial-Temporal ConsistencyCode3
FreeU: Free Lunch in Diffusion U-NetCode3
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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