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 4751–4775 of 4856 papers

TitleStatusHype
Histogram- and Diffusion-Based Medical Out-of-Distribution Detection—0
History-based Anomaly Detector: an Adversarial Approach to Anomaly Detection—0
HLogformer: A Hierarchical Transformer for Representing Log Data—0
HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection—0
Hoi2Anomaly: An Explainable Anomaly Detection Approach Guided by Human-Object Interaction—0
Holistic Features For Real-Time Crowd Behaviour Anomaly Detection—0
Holmes: An Efficient and Lightweight Semantic Based Anomalous Email Detector—0
HomographyAD: Deep Anomaly Detection Using Self Homography Learning—0
Host-based anomaly detection using Eigentraces feature extraction and one-class classification on system call trace data—0
How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection?—0
How Low Can You Go? Surfacing Prototypical In-Distribution Samples for Unsupervised Anomaly Detection—0
How to boost autoencoders?—0
HR-Crime: Human-Related Anomaly Detection in Surveillance Videos—0
HTTP2vec: Embedding of HTTP Requests for Detection of Anomalous Traffic—0
Human Abnormality Detection Based on Bengali Text—0
Human-AI communication for human-human communication: Applying interpretable unsupervised anomaly detection to executive coaching—0
Human-Free Automated Prompting for Vision-Language Anomaly Detection: Prompt Optimization with Meta-guiding Prompt Scheme—0
Human readable network troubleshooting based on anomaly detection and feature scoring—0
Human-Scene Network: A Novel Baseline with Self-rectifying Loss for Weakly supervised Video Anomaly Detection—0
HURRA! Human readable router anomaly detection—0
Hybrid AI-based Anomaly Detection Model using Phasor Measurement Unit Data—0
Hybrid Architecture for Real-Time Video Anomaly Detection: Integrating Spatial and Temporal Analysis—0
Hybrid Attention Networks for Flow and Pressure Forecasting in Water Distribution Systems—0
Hybrid Cloud-Edge Collaborative Data Anomaly Detection in Industrial Sensor Networks—0
Hybrid Cryptocurrency Pump and Dump Detection—0
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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