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 601–650 of 4856 papers

TitleStatusHype
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video DatasetCode1
DiffGAD: A Diffusion-based Unsupervised Graph Anomaly DetectorCode1
Anomaly Detection with Score Distribution DiscriminationCode1
Diffusion for Out-of-Distribution Detection on Road Scenes and BeyondCode1
Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRICode1
Diffusion Models with Implicit Guidance for Medical Anomaly DetectionCode1
Do Language Models Understand Time?Code1
Anomaly Detection of Wind Turbine Time Series using Variational Recurrent AutoencodersCode1
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised LearningCode1
DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detectionCode1
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive LearningCode1
Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour modelsCode1
CHAD: Charlotte Anomaly DatasetCode1
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing FlowsCode1
Dual-Distribution Discrepancy for Anomaly Detection in Chest X-RaysCode1
Anomaly Detection Requires Better RepresentationsCode1
Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly DetectionCode1
Dual-path Frequency Discriminators for Few-shot Anomaly DetectionCode1
Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and AlgorithmsCode1
DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT SystemsCode1
Challenges in Visual Anomaly Detection for Mobile RobotsCode1
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution FunctionsCode1
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly DetectionCode1
Anomaly Detection under Distribution ShiftCode1
Energy TransformerCode1
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged FraudstersCode1
ChatGPT for Digital Forensic Investigation: The Good, The Bad, and The UnknownCode1
Entropy Causal Graphs for Multivariate Time Series Anomaly DetectionCode1
Estimating the Contamination Factor's Distribution in Unsupervised Anomaly DetectionCode1
Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly DetectionCode1
Catching Both Gray and Black Swans: Open-set Supervised Anomaly DetectionCode1
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly DetectionCode1
Explainable Deep Few-shot Anomaly Detection with Deviation NetworksCode1
Explainable Deep One-Class ClassificationCode1
AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and LocalizationCode1
Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography ImagesCode1
Exploring Image Augmentations for Siamese Representation Learning with Chest X-RaysCode1
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and ForecastingCode1
CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event SequencesCode1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly DetectionCode1
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile RobotsCode1
Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale LearningCode1
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly LocalizationCode1
FastAno: Fast Anomaly Detection via Spatio-temporal Patch TransformationCode1
Anomaly Detection using Score-based Perturbation ResilienceCode1
FastDTW is approximate and Generally Slower than the Algorithm it ApproximatesCode1
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly DetectionCode1
Federated Foundation Models on Heterogeneous Time SeriesCode1
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT NetworksCode1
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth SimulationCode1
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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
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
7DDADDetection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9PBASDetection AUROC99.8—Unverified
10HETMMDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4DDADDetection AUROC98.9—Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
6INP-Former ViT-B (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