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 891–900 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case Study	Nov 5, 2023	Anomaly Detection	CodeCode Available	1	5
Learning Generalized Spoof Cues for Face Anti-spoofing	May 8, 2020	Anomaly DetectionDiversity	CodeCode Available	1	5
How To Backdoor Federated Learning	Jul 2, 2018	Anomaly DetectionData Poisoning	CodeCode Available	1	5
Anomaly Detection in Aerial Videos with Transformers	Sep 25, 2022	Anomaly Detection	CodeCode Available	1	5
An Attribute-based Method for Video Anomaly Detection	Dec 1, 2022	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	1	5
HSTforU: anomaly detection in aerial and ground-based videos with hierarchical spatio-temporal transformer for U-net	Jan 3, 2025	Anomaly DetectionDecoder	CodeCode Available	1	5
Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection	Nov 15, 2021	Anomaly DetectionTime Series	CodeCode Available	1	5
Learning Latent Space Energy-Based Prior Model	Jun 15, 2020	Anomaly Detectionmodel	CodeCode Available	1	5
Hybrid Open-set Segmentation with Synthetic Negative Data	Jan 19, 2023	Anomaly DetectionSegmentation	CodeCode Available	1	5
Learning to Adapt to Unseen Abnormal Activities under Weak Supervision	Mar 25, 2022	Anomaly DetectionMeta-Learning	CodeCode Available	1	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