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 1941–1950 of 4856 papers

Title	Date	Tasks	Status
Evaluation of Point Pattern Features for Anomaly Detection of Defect within Random Finite Set Framework	Feb 3, 2021	Anomaly DetectionDefect Detection	—Unverified
Automated, real-time hospital ICU emergency signaling: A field-level implementation	Nov 3, 2021	Anomaly Detection	—Unverified
Evaluation Pipeline for systematically searching for Anomaly Detection Systems	Jun 18, 2025	Anomaly Detection	—Unverified
Evaluation Strategy of Time-series Anomaly Detection with Decay Function	May 15, 2023	Anomaly DetectionTime Series	—Unverified
EvAn: Neuromorphic Event-based Anomaly Detection	Nov 21, 2019	Anomaly DetectionGenerative Adversarial Network	—Unverified
EVA-S2PLoR: A Secure Element-wise Multiplication Meets Logistic Regression on Heterogeneous Database	Jan 9, 2025	Anomaly DetectionPrivacy Preserving	—Unverified
Event2Graph: Event-driven Bipartite Graph for Multivariate Time-series Anomaly Detection	Aug 15, 2021	Anomaly DetectionTime Series	—Unverified
Event and Anomaly Detection Using Tucker3 Decomposition	Jun 12, 2014	Anomaly Detection	—Unverified
Event-Based Dynamic Banking Network Exploration for Economic Anomaly Detection	Mar 4, 2021	Anomaly Detection	—Unverified
Crowd Scene Analysis using Deep Learning Techniques	May 13, 2025	Anomaly DetectionBinary Classification	—Unverified

Show:10 25 50

← PrevPage 195 of 486Next →

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