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 521–530 of 4856 papers

Title	Date	Tasks	Status	Hype
On the Adversarial Robustness of Benjamini Hochberg	Jan 6, 2025	Adversarial RobustnessAnomaly Detection	—Unverified	0
GraphDART: Graph Distillation for Efficient Advanced Persistent Threat Detection	Jan 6, 2025	Anomaly DetectionComputational Efficiency	—Unverified	0
Unsupervised Tomato Split Anomaly Detection using Hyperspectral Imaging and Variational Autoencoders	Jan 6, 2025	Anomaly Detection	—Unverified	0
Self-Supervised Learning for Detecting AI-Generated Faces as Anomalies	Jan 4, 2025	Anomaly DetectionBinary Classification	CodeCode Available	0
HSTforU: anomaly detection in aerial and ground-based videos with hierarchical spatio-temporal transformer for U-net	Jan 3, 2025	Anomaly DetectionDecoder	CodeCode Available	1
Counterfactual Explanation for Auto-Encoder Based Time-Series Anomaly Detection	Jan 3, 2025	Anomaly Detectioncounterfactual	—Unverified	0
Multivariate Time Series Anomaly Detection using DiffGAN Model	Jan 3, 2025	Anomaly DetectionGenerative Adversarial Network	CodeCode Available	0
LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction	Jan 3, 2025	Anomaly DetectionVisual Reasoning	—Unverified	0
Training Medical Large Vision-Language Models with Abnormal-Aware Feedback	Jan 2, 2025	Anomaly DetectionVisual Localization	—Unverified	0
InDeed: Interpretable image deep decomposition with guaranteed generalizability	Jan 2, 2025	Anomaly DetectionDenoising	—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