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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2301–2325 of 7282 papers

TitleStatusHype
Scaling Diffusion Models to Real-World 3D LiDAR Scene CompletionCode3
IIDM: Image-to-Image Diffusion Model for Semantic Image SynthesisCode0
Eigen-CNN: Eigenimages Plus Eigennoise Level Maps Guided Network for Hyperspectral Image DenoisingCode0
Generalized Consistency Trajectory Models for Image ManipulationCode1
Depth-guided NeRF Training via Earth Mover's Distance—0
WaveFace: Authentic Face Restoration with Efficient Frequency Recovery—0
Low-Trace Adaptation of Zero-shot Self-supervised Blind Image Denoising—0
VQ-NeRV: A Vector Quantized Neural Representation for VideosCode1
You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANsCode2
Tuning-Free Image Customization with Image and Text GuidanceCode2
One-Step Image Translation with Text-to-Image ModelsCode7
denoiSplit: a method for joint microscopy image splitting and unsupervised denoising—0
VideoMV: Consistent Multi-View Generation Based on Large Video Generative Model—0
Divide-and-Conquer Posterior Sampling for Denoising Diffusion PriorsCode1
Certified Robustness to Clean-Label Poisoning Using Diffusion Denoising—0
Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly DetectionCode1
WIA-LD2ND: Wavelet-based Image Alignment for Self-supervised Low-Dose CT DenoisingCode1
VmambaIR: Visual State Space Model for Image RestorationCode3
Adaptive Semantic-Enhanced Denoising Diffusion Probabilistic Model for Remote Sensing Image Super-ResolutionCode1
StableGarment: Garment-Centric Generation via Stable Diffusion—0
MicroDiffusion: Implicit Representation-Guided Diffusion for 3D Reconstruction from Limited 2D Microscopy ProjectionsCode2
OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion ModelsCode4
A Spectrum-based Image Denoising Method with Edge Feature Enhancement—0
stMCDI: Masked Conditional Diffusion Model with Graph Neural Network for Spatial Transcriptomics Data Imputation—0
Denoising Task Difficulty-based Curriculum for Training Diffusion Models—0
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified