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 3501–3510 of 4856 papers

Title	Date	Tasks	Status	Hype
Multicalibrated Partitions for Importance Weights	Mar 10, 2021	Anomaly DetectionDomain Adaptation	—Unverified	0
Multi-Class Multiple Instance Learning for Predicting Precursors to Aviation Safety Events	Mar 10, 2021	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
Towards automated brain aneurysm detection in TOF-MRA: open data, weak labels, and anatomical knowledge	Mar 10, 2021	Anomaly DetectionSensitivity	CodeCode Available	1
Pixel-wise Anomaly Detection in Complex Driving Scenes	Mar 9, 2021	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1
ZYELL-NCTU NetTraffic-1.0: A Large-Scale Dataset for Real-World Network Anomaly Detection	Mar 8, 2021	Anomaly DetectionIntrusion Detection	—Unverified	0
Anomaly Detection Based on Selection and Weighting in Latent Space	Mar 8, 2021	Anomaly Detection	—Unverified	0
Student-Teacher Feature Pyramid Matching for Anomaly Detection	Mar 7, 2021	Anomaly Detectionimage-classification	CodeCode Available	1
Anomaly detection and automatic labeling for solar cell quality inspection based on Generative Adversarial Network	Mar 5, 2021	Anomaly DetectionDefect Detection	—Unverified	0
Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images	Mar 5, 2021	Anomaly DetectionContrastive Learning	CodeCode Available	1
FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation	Mar 5, 2021	AnatomyAnomaly Detection	—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	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