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 1241–1250 of 4856 papers

Title	Date	Tasks	Status	Score
A Multi-task Deep Learning Architecture for Maritime Surveillance using AIS Data Streams	Jun 6, 2018	Anomaly DetectionDeep Learning	CodeCode Available	5
Generative Optimization Networks for Memory Efficient Data Generation	Oct 6, 2021	Anomaly DetectionTime Series	CodeCode Available	5
GeoTrackNet-A Maritime Anomaly Detector using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection	Dec 2, 2019	Anomaly Detection	CodeCode Available	5
GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model	Mar 23, 2025	Anomaly DetectionDrug Discovery	CodeCode Available	5
Graph Embedded Pose Clustering for Anomaly Detection	Dec 26, 2019	Anomaly DetectionClustering	CodeCode Available	5
Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural Networks	May 17, 2024	Anomaly DetectionData Augmentation	CodeCode Available	5
Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series	Sep 13, 2018	Anomaly DetectionTime Series	CodeCode Available	5
General Domain Adaptation Through Proportional Progressive Pseudo Labeling	Dec 23, 2020	Anomaly DetectionDomain Adaptation	CodeCode Available	5
Anomaly Detection with Density Estimation	Jan 14, 2020	Anomaly DetectionDensity Estimation	CodeCode Available	5
GDformer: Going Beyond Subsequence Isolation for Multivariate Time Series Anomaly Detection	Jan 30, 2025	Anomaly DetectionTime Series	CodeCode Available	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