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 1501–1525 of 7282 papers

TitleStatusHype
ASD-Diffusion: Anomalous Sound Detection with Diffusion Models—0
Neural Differential Appearance EquationsCode1
Mixture of Efficient Diffusion Experts Through Automatic Interval and Sub-Network Selection—0
S^2AG-Vid: Enhancing Multi-Motion Alignment in Video Diffusion Models via Spatial and Syntactic Attention-Based Guidance—0
EDGE-Rec: Efficient and Data-Guided Edge Diffusion For Recommender Systems Graphs—0
Quantitative and Qualitative Evaluation of NLM and Wavelet Methods in Image Enhancement—0
Anisotropic Diffusion Probabilistic Model for Imbalanced Image Classification—0
A Large Language Model and Denoising Diffusion Framework for Targeted Design of Microstructures with Commands in Natural Language—0
DS2TA: Denoising Spiking Transformer with Attenuated Spatiotemporal Attention—0
PTQ4ADM: Post-Training Quantization for Efficient Text Conditional Audio Diffusion Models—0
High-dimensional learning of narrow neural networks—0
Nonlinear Inverse Design of Mechanical Multi-Material Metamaterials Enabled by Video Denoising Diffusion and Structure Identifier—0
DenoMamba: A fused state-space model for low-dose CT denoisingCode1
HSIGene: A Foundation Model For Hyperspectral Image GenerationCode2
Denoising Reuse: Exploiting Inter-frame Motion Consistency for Efficient Video Latent Generation—0
When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising RecommendationCode0
Unrolled denoising networks provably learn optimal Bayesian inference—0
Massively Multi-Person 3D Human Motion Forecasting with Scene ContextCode1
Denoising diffusion models for high-resolution microscopy image restoration—0
Agent Aggregator with Mask Denoise Mechanism for Histopathology Whole Slide Image Analysis—0
GUNet: A Graph Convolutional Network United Diffusion Model for Stable and Diversity Pose Generation—0
Noise-aware Dynamic Image Denoising and Positron Range Correction for Rubidium-82 Cardiac PET Imaging via Self-supervision—0
Ultrasound Image Enhancement with the Variance of Diffusion ModelsCode1
Edge-based Denoising Image Compression—0
Enhanced segmentation of femoral bone metastasis in CT scans of patients using synthetic data generation with 3D 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