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	CPR-faster(TensorRT)	FPS	1,016	—	Unverified
2	CPR-fast(TensorRT)	FPS	362	—	Unverified
3	CPR(TensorRT)	FPS	130	—	Unverified
4	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UniNet	Detection AUROC	99.8	—	Unverified
2	GLAD	Detection AUROC	99.5	—	Unverified
3	UniNet(model-unified multi-class)	Detection AUROC	99.15	—	Unverified
4	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	Detection AUROC	98.8	—	Unverified
9	TransFusion	Detection AUROC	98.7	—	Unverified
10	HETMM	Detection AUROC	98.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CSAD	Avg. Detection AUROC	95.3	—	Unverified
2	PSAD	Avg. Detection AUROC	94.9	—	Unverified