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 3811–3820 of 4856 papers

Title	Date	Tasks	Status	Hype
Detection of Abnormal Vessel Behaviours from AIS data using GeoTrackNet: from the Laboratory to the Ocean	Aug 12, 2020	Anomaly Detection	—Unverified	0
Learning to Detect Anomalous Wireless Links in IoT Networks	Aug 12, 2020	Anomaly Detection	—Unverified	0
Anomaly localization by modeling perceptual features	Aug 12, 2020	Anomaly DetectionAnomaly Localization	CodeCode Available	1
Exposing Deep-faked Videos by Anomalous Co-motion Pattern Detection	Aug 11, 2020	Anomaly DetectionData Compression	—Unverified	0
ARCADe: A Rapid Continual Anomaly Detector	Aug 10, 2020	Anomaly Detectioncontinual anomaly detection	CodeCode Available	1
Encoding Structure-Texture Relation with P-Net for Anomaly Detection in Retinal Images	Aug 9, 2020	AnatomyAnomaly Detection	CodeCode Available	1
Bayesian Optimization with Machine Learning Algorithms Towards Anomaly Detection	Aug 5, 2020	Anomaly DetectionBayesian Optimization	—Unverified	0
A Causal-based Framework for Multimodal Multivariate Time Series Validation Enhanced by Unsupervised Deep Learning as an Enabler for Industry 4.0	Aug 5, 2020	Anomaly DetectionCausal Discovery	—Unverified	0
Interpretable Anomaly Detection with Mondrian Pólya Forests on Data Streams	Aug 4, 2020	Anomaly Detection	—Unverified	0
Learning Based Methods for Traffic Matrix Estimation from Link Measurements	Aug 3, 2020	Anomaly DetectionGenerative Adversarial Network	—Unverified	0

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