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 2001–2025 of 7282 papers

TitleStatusHype
Wasserstein Convergence of Score-based Generative Models under Semiconvexity and Discontinuous Gradients—0
MRI motion correction via efficient residual-guided denoising diffusion probabilistic models—0
Coop-WD: Cooperative Perception with Weighting and Denoising for Robust V2V Communication—0
Enhancing Glass Defect Detection with Diffusion Models: Addressing Imbalanced Datasets in Manufacturing Quality Control—0
Plug-and-Play AMC: Context Is King in Training-Free, Open-Set Modulation with LLMsCode0
Dual Prompting for Diverse Count-level PET Denoising—0
Quantizing Diffusion Models from a Sampling-Aware Perspective—0
DualReal: Adaptive Joint Training for Lossless Identity-Motion Fusion in Video Customization—0
Enhancing Black-Litterman Portfolio via Hybrid Forecasting Model Combining Multivariate Decomposition and Noise Reduction—0
Edge-preserving Image Denoising via Multi-scale Adaptive Statistical Independence Testing—0
AI-Driven Segmentation and Analysis of Microbial Cells—0
A Time-Series Data Augmentation Model through Diffusion and Transformer Integration—0
Generative diffusion model surrogates for mechanistic agent-based biological models—0
Safety-Critical Traffic Simulation with Guided Latent Diffusion Model—0
Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution—0
MagicPortrait: Temporally Consistent Face Reenactment with 3D Geometric GuidanceCode0
GarmentDiffusion: 3D Garment Sewing Pattern Generation with Multimodal Diffusion Transformers—0
DiffusionRIR: Room Impulse Response Interpolation using Diffusion Models—0
Adept: Annotation-Denoising Auxiliary Tasks with Discrete Cosine Transform Map and Keypoint for Human-Centric Pretraining—0
Outlier-aware Tensor Robust Principal Component Analysis with Self-guided Data Augmentation—0
HepatoGEN: Generating Hepatobiliary Phase MRI with Perceptual and Adversarial Models—0
Generative AI for Physical-Layer Authentication—0
Evolution Meets Diffusion: Efficient Neural Architecture Generation—0
A Machine Learning Approach for Denoising and Upsampling HRTFs—0
Fast Autoregressive Models for Continuous Latent Generation—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