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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 251–275 of 4856 papers

TitleStatusHype
PHEVA: A Privacy-preserving Human-centric Video Anomaly Detection DatasetCode1
Time Series Analysis for Education: Methods, Applications, and Future DirectionsCode1
Variational Autoencoder for Anomaly Detection: A Comparative StudyCode1
Multivariate Time-Series Anomaly Detection based on Enhancing Graph Attention Networks with Topological AnalysisCode1
UMAD: University of Macau Anomaly Detection Benchmark DatasetCode1
ADformer: A Multi-Granularity Transformer for EEG-Based Alzheimer's Disease AssessmentCode1
Deep Generative Classification of Blood Cell MorphologyCode1
Small Object Few-shot Segmentation for Vision-based Industrial InspectionCode1
Diffusion for Out-of-Distribution Detection on Road Scenes and BeyondCode1
R3D-AD: Reconstruction via Diffusion for 3D Anomaly DetectionCode1
Federated PCA on Grassmann Manifold for IoT Anomaly DetectionCode1
ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open Radio Access NetworksCode1
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video DatasetCode1
SOWA: Adapting Hierarchical Frozen Window Self-Attention to Visual-Language Models for Better Anomaly DetectionCode1
HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly DetectionCode1
LogEval: A Comprehensive Benchmark Suite for Large Language Models In Log AnalysisCode1
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based ModelsCode1
The OPS-SAT benchmark for detecting anomalies in satellite telemetryCode1
Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly DetectionCode1
Looking 3D: Anomaly Detection with 2D-3D AlignmentCode1
VideoVista: A Versatile Benchmark for Video Understanding and ReasoningCode1
Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided MaskCode1
VANE-Bench: Video Anomaly Evaluation Benchmark for Conversational LMMsCode1
Cross-Modal Learning for Anomaly Detection in Complex Industrial Process: Methodology and BenchmarkCode1
Few-Shot Anomaly Detection via Category-Agnostic Registration LearningCode1
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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