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 1081–1090 of 4856 papers

Title	Date	Tasks	Status
A Typology of Data Anomalies	Jul 4, 2021	Anomaly Detection	—Unverified
Anomaly Detection Based on Aggregation of Indicators	Jul 3, 2014	Anomaly Detectionfeature selection	—Unverified
A Federated Learning Approach to Anomaly Detection in Smart Buildings	Oct 20, 2020	Anomaly DetectionFederated Learning	—Unverified
Evolutionary Optimization of 1D-CNN for Non-contact Respiration Pattern Classification	Dec 20, 2023	Anomaly DetectionClassification	—Unverified
Computer Vision on X-ray Data in Industrial Production and Security Applications: A Comprehensive Survey	Nov 10, 2022	Anomaly Detection	—Unverified
Concept Drift Challenge in Multimedia Anomaly Detection: A Case Study with Facial Datasets	Jul 27, 2022	Anomaly Detection	—Unverified
A Tube-and-Droplet-based Approach for Representing and Analyzing Motion Trajectories	Sep 10, 2016	3D Action RecognitionAction Recognition	—Unverified
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models	Jul 30, 2020	Anomaly DetectionTime Series	—Unverified
Attire-Based Anomaly Detection in Restricted Areas Using YOLOv8 for Enhanced CCTV Security	Mar 31, 2024	Anomaly Detectionobject-detection	—Unverified
Attention to Patterns is all you need for Insider threat detection	Oct 26, 2024	AllAnomaly 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