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 1191–1200 of 4856 papers

Title	Date	Tasks	Status	Score
Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing Values	Jan 11, 2024	Anomaly DetectionMissing Values	CodeCode Available	5
A Novel Multi-Stage Approach for Hierarchical Intrusion Detection	Mar 21, 2023	Anomaly DetectionIntrusion Detection	CodeCode Available	5
A Novel Center-based Deep Contrastive Metric Learning Method for the Detection of Polymicrogyria in Pediatric Brain MRI	Nov 22, 2022	Anomaly DetectionMetric Learning	CodeCode Available	5
Graph Laplacian for Image Anomaly Detection	Feb 27, 2018	Anomaly Detection	CodeCode Available	5
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection	Mar 18, 2019	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	5
An Autoencoder Architecture for L-band Passive Microwave Retrieval of Landscape Freeze-Thaw Cycle	Jul 4, 2024	Anomaly DetectionRetrieval	CodeCode Available	5
Graph Embedded Pose Clustering for Anomaly Detection	Dec 26, 2019	Anomaly DetectionClustering	CodeCode Available	5
Good Practices and A Strong Baseline for Traffic Anomaly Detection	May 9, 2021	Anomaly DetectionManagement	CodeCode Available	5
GradStop: Exploring Training Dynamics in Unsupervised Outlier Detection through Gradient	Dec 11, 2024	Anomaly DetectionOutlier Detection	CodeCode Available	5
Graph Fairing Convolutional Networks for Anomaly Detection	Oct 20, 2020	Anomaly DetectionSemi-supervised Anomaly 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