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 1121–1130 of 4856 papers

Title	Date	Tasks	Status	Score
Hybrid Deep Network for Anomaly Detection	Aug 17, 2019	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	5
Human Kinematics-inspired Skeleton-based Video Anomaly Detection	Sep 27, 2023	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	5
Hybrid Deep Neural Networks to Infer State Models of Black-Box Systems	Aug 26, 2020	Anomaly DetectionC++ code	CodeCode Available	5
HyperBrain: Anomaly Detection for Temporal Hypergraph Brain Networks	Oct 2, 2024	Anomaly DetectionGraph Learning	CodeCode Available	5
HSS-IAD: A Heterogeneous Same-Sort Industrial Anomaly Detection Dataset	Apr 17, 2025	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	5
ARES: Locally Adaptive Reconstruction-based Anomaly Scoring	Jun 15, 2022	Anomaly DetectionDimensionality Reduction	CodeCode Available	5
Hyperedge Anomaly Detection with Hypergraph Neural Network	Dec 7, 2024	Anomaly DetectionLink Prediction	CodeCode Available	5
Image-Based Detection of Modifications in Gas Pump PCBs with Deep Convolutional Autoencoders	Sep 30, 2022	Anomaly DetectionAnomaly Segmentation	CodeCode Available	5
Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks	Apr 16, 2021	Anomaly DetectionSelf-Supervised Anomaly Detection	CodeCode Available	5
How to Allocate your Label Budget? Choosing between Active Learning and Learning to Reject in Anomaly Detection	Jan 7, 2023	Active LearningAnomaly Detection	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