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 3061–3070 of 4856 papers

Title	Date	Tasks	Status	Hype
Auditing Keyword Queries Over Text Documents	Dec 1, 2021	Anomaly Detection	—Unverified	0
Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery	Dec 1, 2021	Anomaly DetectionFault Detection	—Unverified	0
CLAWS: Contrastive Learning with hard Attention and Weak Supervision	Dec 1, 2021	Anomaly DetectionContrastive Learning	—Unverified	0
Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation	Dec 1, 2021	Anomaly DetectionGraph Neural Network	CodeCode Available	1
TiWS-iForest: Isolation Forest in Weakly Supervised and Tiny ML scenarios	Nov 30, 2021	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	0
Reconstruction Student with Attention for Student-Teacher Pyramid Matching	Nov 30, 2021	Anomaly Detection	—Unverified	0
A novel data-driven algorithm to predict anomalous prescription based on patient's feature set	Nov 30, 2021	Anomaly Detection	—Unverified	0
Anomaly-Aware Semantic Segmentation by Leveraging Synthetic-Unknown Data	Nov 29, 2021	Anomaly DetectionAnomaly Segmentation	—Unverified	0
Anomaly Rule Detection in Sequence Data	Nov 29, 2021	Anomaly DetectionOutlier Detection	—Unverified	0
Automated Antenna Testing Using Encoder-Decoder-based Anomaly Detection	Nov 27, 2021	Anomaly DetectionDecoder	—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