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

Showing 426450 of 4856 papers

TitleStatusHype
BSDM: Background Suppression Diffusion Model for Hyperspectral Anomaly DetectionCode1
Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly DetectionCode1
Masked Autoencoders for Unsupervised Anomaly Detection in Medical ImagesCode1
Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly DetectionCode1
PKU-GoodsAD: A Supermarket Goods Dataset for Unsupervised Anomaly Detection and SegmentationCode1
ChatGPT for Digital Forensic Investigation: The Good, The Bad, and The UnknownCode1
DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT SystemsCode1
Unsupervised Video Anomaly Detection with Diffusion Models Conditioned on Compact Motion RepresentationsCode1
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly DetectionCode1
Graph-level Anomaly Detection via Hierarchical Memory NetworksCode1
Graph Neural Networks based Log Anomaly Detection and ExplanationCode1
Precursor-of-Anomaly Detection for Irregular Time SeriesCode1
Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly DetectionCode1
Anomaly Detection with Score Distribution DiscriminationCode1
Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly DetectorsCode1
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly DetectionCode1
BMAD: Benchmarks for Medical Anomaly DetectionCode1
Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public ProcurementCode1
Improving Generalizability of Graph Anomaly Detection Models via Data AugmentationCode1
ReContrast: Domain-Specific Anomaly Detection via Contrastive ReconstructionCode1
UADB: Unsupervised Anomaly Detection BoosterCode1
AlerTiger: Deep Learning for AI Model Health Monitoring at LinkedInCode1
GAD-NR: Graph Anomaly Detection via Neighborhood ReconstructionCode1
Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion ModelCode1
Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection through Automatic Diffusion ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified