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 1961–1970 of 4856 papers

Title	Date	Tasks	Status
Automatic Prompt Generation and Grounding Object Detection for Zero-Shot Image Anomaly Detection	Nov 28, 2024	Anomaly DetectionImage-text matching	—Unverified
Experiments on Anomaly Detection in Autonomous Driving by Forward-Backward Style Transfers	Jul 13, 2022	Anomaly DetectionAutonomous Driving	—Unverified
Expert enhanced dynamic time warping based anomaly detection	Oct 2, 2023	Anomaly DetectionDynamic Time Warping	—Unverified
Explainable AI (XAI) for PHM of Industrial Asset: A State-of-The-Art, PRISMA-Compliant Systematic Review	Jul 8, 2021	Anomaly DetectionArticles	—Unverified
An Adaptive Event-based Data Converter for Always-on Biomedical Applications at the Edge	Nov 23, 2022	Anomaly Detection	—Unverified
Explainable Anomaly Detection: Counterfactual driven What-If Analysis	Aug 21, 2024	Anomaly Detectioncounterfactual	—Unverified
FetalFlex: Anatomy-Guided Diffusion Model for Flexible Control on Fetal Ultrasound Image Synthesis	Mar 19, 2025	AnatomyAnomaly Detection	—Unverified
Few-shot Anomaly Detection in Text with Deviation Learning	Aug 22, 2023	Anomaly DetectionFew-Shot Learning	—Unverified
Crowd Scene Analysis using Deep Learning Techniques	May 13, 2025	Anomaly DetectionBinary Classification	—Unverified
Crowd-level Abnormal Behavior Detection via Multi-scale Motion Consistency Learning	Dec 1, 2022	Anomaly DetectionVideo Anomaly Detection	—Unverified

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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	GLASS	Detection AUROC	99.9	—	Unverified
5	UniNet	Detection AUROC	99.9	—	Unverified
6	HETMM	Detection AUROC	99.8	—	Unverified
7	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	PBAS	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	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	DDAD	Detection AUROC	98.9	—	Unverified
6	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
7	DiffusionAD	Detection AUROC	98.8	—	Unverified
8	GLASS	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