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 531–540 of 4856 papers

Title	Date	Tasks	Status	Hype
Lorentz group equivariant autoencoders	Dec 14, 2022	Anomaly Detection	CodeCode Available	1
CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly Detection	Dec 9, 2022	Anomaly DetectionMultiple Instance Learning	CodeCode Available	1
On Root Cause Localization and Anomaly Mitigation through Causal Inference	Dec 8, 2022	Anomaly DetectionCausal Inference	CodeCode Available	1
Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignment	Dec 2, 2022	Anomaly DetectionContrastive Learning	CodeCode Available	1
An Attribute-based Method for Video Anomaly Detection	Dec 1, 2022	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	1
MGFN: Magnitude-Contrastive Glance-and-Focus Network for Weakly-Supervised Video Anomaly Detection	Nov 28, 2022	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation	Nov 26, 2022	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1
RbA: Segmenting Unknown Regions Rejected by All	Nov 25, 2022	AllAnomaly Detection	CodeCode Available	1
MAEDAY: MAE for few and zero shot AnomalY-Detection	Nov 25, 2022	Anomaly DetectionImage Inpainting	CodeCode Available	1
PNI : Industrial Anomaly Detection using Position and Neighborhood Information	Nov 22, 2022	Anomaly DetectionOutlier Detection	CodeCode Available	1

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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