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 3631–3640 of 4856 papers

Title	Date	Tasks	Status	Hype
Comparison of Anomaly Detectors: Context Matters	Dec 11, 2020	Anomaly DetectionModel Selection	CodeCode Available	0
Water Level Estimation Using Sentinel-1 Synthetic Aperture Radar Imagery And Digital Elevation Models	Dec 11, 2020	Anomaly Detection	—Unverified	0
MOCCA: Multi-Layer One-Class ClassificAtion for Anomaly Detection	Dec 9, 2020	Anomaly DetectionClassification	CodeCode Available	1
Deep Unsupervised Image Anomaly Detection: An Information Theoretic Framework	Dec 9, 2020	Anomaly Detection	—Unverified	0
A Deep Learning Approach to Anomaly Sequence Detection for High-Resolution Monitoring of Power Systems	Dec 9, 2020	Anomaly DetectionGenerative Adversarial Network	—Unverified	0
Modeling asset allocation strategies and a new portfolio performance score	Dec 9, 2020	Anomaly DetectionManagement	—Unverified	0
JANUS: Benchmarking Commercial and Open-Source Cloud and Edge Platforms for Object and Anomaly Detection Workloads	Dec 9, 2020	Anomaly DetectionBenchmarking	—Unverified	0
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification	Dec 9, 2020	Anomaly DetectionAtrial Fibrillation Detection	CodeCode Available	1
ESAD: End-to-end Deep Semi-supervised Anomaly Detection	Dec 9, 2020	Anomaly DetectionDecoder	—Unverified	0
Removing Class Imbalance using Polarity-GAN: An Uncertainty Sampling Approach	Dec 9, 2020	Anomaly DetectionGenerative Adversarial Network	—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