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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1–10 of 4856 papers

Title	Date	Tasks	Status	Hype
Multi-Stage Prompt Inference Attacks on Enterprise LLM Systems	Jul 21, 2025	Anomaly Detection	—Unverified	0
3DKeyAD: High-Resolution 3D Point Cloud Anomaly Detection via Keypoint-Guided Point Clustering	Jul 17, 2025	Anomaly DetectionAnomaly Localization	—Unverified	0
A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys	Jul 17, 2025	Anomaly DetectionSelf-Supervised Learning	—Unverified	0
A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy	Jul 16, 2025	Anomaly DetectionFederated Learning	—Unverified	0
Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection	Jul 15, 2025	Anomaly ClassificationAnomaly Detection	—Unverified	0
Adversarial Activation Patching: A Framework for Detecting and Mitigating Emergent Deception in Safety-Aligned Transformers	Jul 12, 2025	Anomaly Detection	—Unverified	0
Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects	Jul 10, 2025	3D Anomaly DetectionAnomaly Detection	CodeCode Available	2
Hyperspectral Anomaly Detection Methods: A Survey and Comparative Study	Jul 8, 2025	Anomaly DetectionBenchmarking	—Unverified	0
seMCD: Sequentially implemented Monte Carlo depth computation with statistical guarantees	Jul 8, 2025	Anomaly Detection	—Unverified	0
What ZTF Saw Where Rubin Looked: Anomaly Hunting in DR23	Jul 8, 2025	Anomaly Detection	—Unverified	0

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All datasets MVTec AD VisA MVTec LOCO AD One-class CIFAR-10 CUHK Avenue ShanghaiTech Fishyscapes L&F UCR Anomaly Archive MPDD BTAD One-class CIFAR-100 UBnormal

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	GeneralAD	AUROC	98.4	—	Unverified
2	Transformaly	AUROC	97.7	—	Unverified
3	PANDA-OE	AUROC	97.3	—	Unverified
4	Mean-Shifted Contrastive Loss	AUROC	96.5	—	Unverified
5	PANDA	AUROC	94.1	—	Unverified
6	CSI	AUROC	89.6	—	Unverified
7	GAN based Anomaly Detection in Imbalance Problems	AUROC	87.4	—	Unverified
8	DisAug CLR	AUROC	86.5	—	Unverified
9	DUIAD	AUROC	86	—	Unverified
10	Rotation Prediction	AUROC	84.1	—	Unverified