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 631–640 of 4856 papers

Title	Date	Tasks	Status	Hype
Deep Learning, Machine Learning, Advancing Big Data Analytics and Management	Dec 3, 2024	Anomaly DetectionDeep Learning	—Unverified	0
An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction	Dec 3, 2024	Anomaly DetectionDecision Making	—Unverified	0
F-SE-LSTM: A Time Series Anomaly Detection Method with Frequency Domain Information	Dec 3, 2024	Anomaly DetectionTime Series	CodeCode Available	1
VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models	Dec 2, 2024	Anomaly DetectionVideo Anomaly Detection	—Unverified	0
Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515	Dec 2, 2024	Anomaly DetectionAstronomy	CodeCode Available	0
Deep evolving semi-supervised anomaly detection	Dec 1, 2024	Anomaly DetectionContinual Learning	—Unverified	0
Exploring Large Vision-Language Models for Robust and Efficient Industrial Anomaly Detection	Dec 1, 2024	Anomaly DetectionAnomaly Localization	—Unverified	0
Vision Technologies with Applications in Traffic Surveillance Systems: A Holistic Survey	Nov 30, 2024	Anomaly Detectionobject-detection	—Unverified	0
Friend or Foe? Harnessing Controllable Overfitting for Anomaly Detection	Nov 30, 2024	Anomaly DetectionMulti-class Anomaly Detection	—Unverified	0
Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data	Nov 29, 2024	Anomaly DetectionTime Series	—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	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