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

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Showing 4201–4210 of 4856 papers

Title	Date	Tasks	Status
Approaches Toward Physical and General Video Anomaly Detection	Dec 14, 2021	Anomaly DetectionDensity Estimation	CodeCode Available
Introduction to Rare-Event Predictive Modeling for Inferential Statisticians -- A Hands-On Application in the Prediction of Breakthrough Patents	Mar 30, 2020	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available
Interruptions detection in video conferences	Feb 25, 2023	Anomaly Detection	CodeCode Available
A Parameter-Efficient Quantum Anomaly Detection Method on a Superconducting Quantum Processor	Dec 22, 2024	Anomaly DetectionQuantum Machine Learning	CodeCode Available
Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models	Jun 30, 2022	Anomaly Detection	CodeCode Available
Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking Study	Feb 11, 2024	Anomaly DetectionBenchmarking	CodeCode Available
TRANSIT your events into a new mass: Fast background interpolation for weakly-supervised anomaly searches	Mar 6, 2025	Anomaly Detection	CodeCode Available
Digital Twin-Based Multiple Access Optimization and Monitoring via Model-Driven Bayesian Learning	Oct 11, 2022	Anomaly DetectionMulti-agent Reinforcement Learning	CodeCode Available
Digital Twin-based Anomaly Detection with Curriculum Learning in Cyber-physical Systems	Sep 27, 2023	Anomaly Detection	CodeCode Available
Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks	May 13, 2023	Anomaly Detection	CodeCode Available

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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