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 2871–2880 of 4856 papers

Title	Date	Tasks	Status
Siamese Transition Masked Autoencoders as Uniform Unsupervised Visual Anomaly Detector	Nov 1, 2022	Anomaly DetectionDecoder	—Unverified
Teacher-Student Network for 3D Point Cloud Anomaly Detection with Few Normal Samples	Oct 31, 2022	3D Anomaly DetectionAnomaly Detection	—Unverified
SoK: Modeling Explainability in Security Analytics for Interpretability, Trustworthiness, and Usability	Oct 31, 2022	Anomaly DetectionDecision Making	—Unverified
Classical ensemble of Quantum-classical ML algorithms for Phishing detection in Ethereum transaction networks	Oct 30, 2022	Anomaly DetectionBenchmarking	CodeCode Available
Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery	Oct 29, 2022	Anomaly DetectionSegmentation	—Unverified
Learning to Detect Interesting Anomalies	Oct 28, 2022	Active LearningAnomaly Detection	—Unverified
Anomaly Detection in Additive Manufacturing Processes using Supervised Classification with Imbalanced Sensor Data based on Generative Adversarial Network	Oct 28, 2022	Anomaly DetectionData Augmentation	—Unverified
Deep Learning-Based Anomaly Detection in Synthetic Aperture Radar Imaging	Oct 28, 2022	Anomaly DetectionChange Detection	—Unverified
Masked Transformer for image Anomaly Localization	Oct 27, 2022	Anomaly DetectionAnomaly Localization	—Unverified
Data-Driven Thermal Anomaly Detection in Large Battery Packs	Oct 27, 2022	Anomaly Detection	—Unverified

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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