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 1–25 of 4856 papers

TitleStatusHype
Multi-Stage Prompt Inference Attacks on Enterprise LLM Systems—0
3DKeyAD: High-Resolution 3D Point Cloud Anomaly Detection via Keypoint-Guided Point Clustering—0
A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys—0
A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy—0
Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection—0
Adversarial Activation Patching: A Framework for Detecting and Mitigating Emergent Deception in Safety-Aligned Transformers—0
Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial DefectsCode2
Hyperspectral Anomaly Detection Methods: A Survey and Comparative Study—0
seMCD: Sequentially implemented Monte Carlo depth computation with statistical guarantees—0
What ZTF Saw Where Rubin Looked: Anomaly Hunting in DR23—0
Taming Anomalies with Down-Up Sampling Networks: Group Center Preserving Reconstruction for 3D Anomaly Detection—0
Evaluating Language Models For Threat Detection in IoT Security LogsCode0
mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at ScaleCode0
Process mining-driven modeling and simulation to enhance fault diagnosis in cyber-physical systems—0
Temporal-Aware Graph Attention Network for Cryptocurrency Transaction Fraud Detection—0
Generative Adversarial Evasion and Out-of-Distribution Detection for UAV Cyber-Attacks—0
FastRef:Fast Prototype Refinement for Few-Shot Industrial Anomaly Detection—0
SiM3D: Single-instance Multiview Multimodal and Multisetup 3D Anomaly Detection Benchmark—0
GANet-Seg: Adversarial Learning for Brain Tumor Segmentation with Hybrid Generative Models—0
E-ABIN: an Explainable module for Anomaly detection in BIological NetworksCode0
Joint attitude estimation and 3D neural reconstruction of non-cooperative space objects—0
Benchmarking Unsupervised Strategies for Anomaly Detection in Multivariate Time SeriesCode0
Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning—0
Exact Matrix Seriation through Mathematical Optimization: Stress and Effectiveness-Based ModelsCode0
Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology—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
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