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 401–425 of 4856 papers

TitleStatusHype
Statistically Significant kNNAD by Selective Inference—0
Value Gradient Sampler: Sampling as Sequential Decision MakingCode0
A Survey of Anomaly Detection in Cyber-Physical Systems—0
Positional Encoding in Transformer-Based Time Series Models: A SurveyCode1
Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection—0
WRT-SAM: Foundation Model-Driven Segmentation for Generalized Weld Radiographic Testing—0
Unifying Explainable Anomaly Detection and Root Cause Analysis in Dynamical Systems—0
Towards a Trustworthy Anomaly Detection for Critical Applications through Approximated Partial AUC LossCode0
DCAD-2000: A Multilingual Dataset across 2000+ Languages with Data Cleaning as Anomaly DetectionCode0
Enhanced Anomaly Detection in IoMT Networks using Ensemble AI Models on the CICIoMT2024 Dataset—0
Exploiting Point-Language Models with Dual-Prompts for 3D Anomaly Detection—0
Enhancing anomaly detection with topology-aware autoencoders—0
Federated Learning-Driven Cybersecurity Framework for IoT Networks with Privacy-Preserving and Real-Time Threat Detection Capabilities—0
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly DetectionCode1
Privacy-Preserving Hybrid Ensemble Model for Network Anomaly Detection: Balancing Security and Data Protection—0
Unsupervised Anomaly Detection on Implicit Shape representations for Sarcopenia Detection—0
CurvGAD: Leveraging Curvature for Enhanced Graph Anomaly Detection—0
GenIAS: Generator for Instantiating Anomalies in time Series—0
Out-of-Distribution Detection on Graphs: A SurveyCode1
MAAT: Mamba Adaptive Anomaly Transformer with association discrepancy for time seriesCode1
Advancing Precision Oncology Through Modeling of Longitudinal and Multimodal Data—0
FADE: Forecasting for Anomaly Detection on ECGCode0
Advancing climate model interpretability: Feature attribution for Arctic melt anomalies—0
Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models—0
Towards Copyright Protection for Knowledge Bases of Retrieval-augmented Language Models via Reasoning—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