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 1181–1190 of 4856 papers

Title	Date	Tasks	Status	Score
Grid HTM: Hierarchical Temporal Memory for Anomaly Detection in Videos	May 30, 2022	Anomaly DetectionDeep Learning	CodeCode Available	5
HACD: Harnessing Attribute Semantics and Mesoscopic Structure for Community Detection	Nov 4, 2024	Anomaly DetectionAttribute	CodeCode Available	5
Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural Networks	May 17, 2024	Anomaly DetectionData Augmentation	CodeCode Available	5
An Unsupervised Framework for Anomaly Detection in a Water Treatment System.	Dec 16, 2019	Anomaly DetectionDecoder	CodeCode Available	5
AndroShield: Automated Android Applications Vulnerability Detection, a Hybrid Static and Dynamic Analysis Approach	Oct 22, 2019	Anomaly DetectionMobile Security	CodeCode Available	5
ADKGD: Anomaly Detection in Knowledge Graphs with Dual-Channel Training	Jan 13, 2025	Anomaly DetectionKnowledge Graphs	CodeCode Available	5
Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing Values	Jan 11, 2024	Anomaly DetectionMissing Values	CodeCode Available	5
Hybrid Deep Neural Networks to Infer State Models of Black-Box Systems	Aug 26, 2020	Anomaly DetectionC++ code	CodeCode Available	5
An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos	Jan 9, 2018	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available	5
A Novel Self-Supervised Learning-Based Anomaly Node Detection Method Based on an Autoencoder in Wireless Sensor Networks	Dec 26, 2022	Anomaly DetectionGraph Neural Network	CodeCode Available	5

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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