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 461–470 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications	Sep 23, 2021	Anomaly Detection	CodeCode Available	1	5
Deep and Confident Prediction for Time Series at Uber	Sep 6, 2017	Anomaly DetectionPrediction	CodeCode Available	1	5
Deep Anomaly Detection with Outlier Exposure	Dec 11, 2018	Anomaly DetectionOut-of-Distribution Detection	CodeCode Available	1	5
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection	Feb 3, 2023	Anomaly DetectionDomain Adaptation	CodeCode Available	1	5
Deep Generative Classification of Blood Cell Morphology	Aug 16, 2024	Anomaly DetectionClassification	CodeCode Available	1	5
LAN: Learning Adaptive Neighbors for Real-Time Insider Threat Detection	Mar 14, 2024	Anomaly DetectionGraph structure learning	CodeCode Available	1	5
Deep Dual Support Vector Data Description for Anomaly Detection on Attributed Networks	Sep 1, 2021	Anomaly DetectionAttribute	CodeCode Available	1	5
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds	Jun 18, 2020	Anomaly DetectionTask 2	CodeCode Available	1	5
Efficient Deep CNN-BiLSTM Model for Network Intrusion Detection	Jun 26, 2020	Anomaly DetectionIntrusion Detection	CodeCode Available	1	5
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT	Mar 30, 2021	Anomaly DetectionGraph Neural Network	CodeCode Available	1	5

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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