SOTAVerified

Anomaly Detection

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

Papers

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Showing 1601–1650 of 4856 papers

TitleStatusHype
Ensemble Clustering for Graphs: Comparisons and ApplicationsCode0
Enhancing Visual Perception in Novel Environments via Incremental Data Augmentation Based on Style TransferCode0
Ensembled Cold-Diffusion Restorations for Unsupervised Anomaly DetectionCode0
CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive LearningCode0
Enhancing Time Series Forecasting with Fuzzy Attention-Integrated TransformersCode0
Adaptive Deviation Learning for Visual Anomaly Detection with Data ContaminationCode0
Enhancing Robustness of On-line Learning Models on Highly Noisy DataCode0
Enhancing Unsupervised Anomaly Detection with Score-Guided NetworkCode0
Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of AugmentationCode0
Enhancing Fairness in Unsupervised Graph Anomaly Detection through DisentanglementCode0
TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly DetectionCode0
Enhanced anomaly detection in well log data through the application of ensemble GANsCode0
Bump Hunting in Latent SpaceCode0
AssemAI: Interpretable Image-Based Anomaly Detection for Manufacturing PipelinesCode0
ENCODE: Encoding NetFlows for Network Anomaly DetectionCode0
Building and Interpreting Deep Similarity ModelsCode0
Anomaly Detection in High Dimensional DataCode0
Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offsCode0
Efficient GAN-Based Anomaly DetectionCode0
Rethinking Medical Anomaly Detection in Brain MRI: An Image Quality Assessment PerspectiveCode0
Efficient Model Monitoring for Quality Control in Cardiac Image SegmentationCode0
Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly DetectionCode0
BRUNO: A Deep Recurrent Model for Exchangeable DataCode0
AIDA: Analytic Isolation and Distance-based Anomaly Detection AlgorithmCode0
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality DetectionCode0
Effective and Efficient Representation Learning for Flight TrajectoriesCode0
Early-Stage Anomaly Detection: A Study of Model Performance on Complete vs. Partial FlowsCode0
Bridging 3D Anomaly Localization and Repair via High-Quality Continuous Geometric RepresentationCode0
Are you sure it’s an artifact? Artifact detection and uncertainty quantification in histological imagesCode0
robROSE: A robust approach for dealing with imbalanced data in fraud detectionCode0
Polynomial Selection in Spectral Graph Neural Networks: An Error-Sum of Function Slices ApproachCode0
Breast Cancer Detection Using Convolutional Neural NetworksCode0
E-ABIN: an Explainable module for Anomaly detection in BIological NetworksCode0
Robust Subspace Recovery Layer for Unsupervised Anomaly DetectionCode0
Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep UnrollingCode0
Adaptive NAD: Online and Self-adaptive Unsupervised Network Anomaly DetectorCode0
Detector monitoring with artificial neural networks at the CMS experiment at the CERN Large Hadron ColliderCode0
Rule-Based Error Detection and Correction to Operationalize Movement Trajectory ClassificationCode0
Action Sequence Augmentation for Early Graph-based Anomaly DetectionCode0
Anomaly detection in dynamic networksCode0
SAM-kNN Regressor for Online Learning in Water Distribution NetworksCode0
Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier featuresCode0
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health EpisodesCode0
Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory TracingCode0
Coupled-Space Attacks against Random-Walk-based Anomaly DetectionCode0
AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal PropertiesCode0
Braced Fourier Continuation and Regression for Anomaly DetectionCode0
Bounding Boxes and Probabilistic Graphical Models: Video Anomaly Detection SimplifiedCode0
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated LearningCode0
Adaptive Anomaly Detection in Chaotic Time Series with a Spatially Aware Echo State NetworkCode0
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All datasetsMVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechFishyscapes L&FUCR Anomaly ArchiveMPDDBTADOne-class CIFAR-100UBnormal

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016—Unverified
2CPR-fast(TensorRT)FPS362—Unverified
3CPR(TensorRT)FPS130—Unverified
4GLASSDetection AUROC99.9—Unverified
5UniNetDetection AUROC99.9—Unverified
6HETMMDetection AUROC99.8—Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10PBASDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
5DDADDetection AUROC98.9—Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
7DiffusionADDetection AUROC98.8—Unverified
8GLASSDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified