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 3211–3220 of 4856 papers

Title	Date	Tasks	Status	Hype
Anomaly Detection on IT Operation Series via Online Matrix Profile	Aug 27, 2021	Anomaly DetectionTime Series	—Unverified	0
Multimodal Data Fusion in High-Dimensional Heterogeneous Datasets via Generative Models	Aug 27, 2021	Anomaly DetectionImputation	CodeCode Available	0
TIMo -- A Dataset for Indoor Building Monitoring with a Time-of-Flight Camera	Aug 27, 2021	Anomaly DetectionHuman Detection	—Unverified	0
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework	Aug 27, 2021	Anomaly DetectionDefect Detection	CodeCode Available	1
End-To-End Anomaly Detection for Identifying Malicious Cyber Behavior through NLP-Based Log Embeddings	Aug 27, 2021	Anomaly DetectionFeature Engineering	—Unverified	0
DeepFlow: Abnormal Traffic Flow Detection Using Siamese Networks	Aug 26, 2021	Anomaly DetectionDynamic Time Warping	—Unverified	0
Human readable network troubleshooting based on anomaly detection and feature scoring	Aug 26, 2021	Anomaly Detection	—Unverified	0
Anomaly Detection in Medical Imaging -- A Mini Review	Aug 25, 2021	Anomaly Detection	—Unverified	0
Normal Learning in Videos with Attention Prototype Network	Aug 25, 2021	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	1
Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection	Aug 23, 2021	Anomaly DetectionAttribute	CodeCode Available	1

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