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 1911–1920 of 4856 papers

Title	Date	Tasks	Status	Hype
ECG classification using Deep CNN and Gramian Angular Field	Jul 25, 2023	Anomaly DetectionClassification	—Unverified	0
Sobolev Space Regularised Pre Density Models	Jul 25, 2023	Anomaly DetectionDensity Estimation	—Unverified	0
Unmasking Anomalies in Road-Scene Segmentation	Jul 25, 2023	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1
RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous Supervision	Jul 25, 2023	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available	1
Few-shot 1/a Anomalies Feedback : Damage Vision Mining Opportunity and Embedding Feature Imbalance	Jul 24, 2023	Anomaly Detectionimage-classification	—Unverified	0
AMAE: Adaptation of Pre-Trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays	Jul 24, 2023	Anomaly DetectionOne-Class Classification	—Unverified	0
UniFormaly: Towards Task-Agnostic Unified Framework for Visual Anomaly Detection	Jul 24, 2023	Anomaly DetectionDefect Detection	CodeCode Available	1
Addressing the Impact of Localized Training Data in Graph Neural Networks	Jul 24, 2023	Anomaly DetectionGraph Generation	CodeCode Available	0
Towards Video Anomaly Retrieval from Video Anomaly Detection: New Benchmarks and Model	Jul 24, 2023	Anomaly DetectionRetrieval	CodeCode Available	1
TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models	Jul 23, 2023	Anomaly DetectionDensity Estimation	—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