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 251–260 of 4856 papers

Title	Date	Tasks	Status	Hype
DFR: Deep Feature Reconstruction for Unsupervised Anomaly Segmentation	Dec 13, 2020	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting	Sep 27, 2024	Anomaly DetectionTime Series	CodeCode Available	1
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows	Jul 27, 2021	Anomaly ClassificationAnomaly Detection	CodeCode Available	1
Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection	Mar 28, 2022	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1
Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly Detection	May 23, 2025	Anomaly DetectionMulti-class Anomaly Detection	CodeCode Available	1
CHAD: Charlotte Anomaly Dataset	Dec 19, 2022	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	1
Can Multimodal LLMs Perform Time Series Anomaly Detection?	Feb 25, 2025	Anomaly DetectionIrregular Time Series	CodeCode Available	1
A Comprehensive Survey on Graph Anomaly Detection with Deep Learning	Jun 14, 2021	Anomaly DetectionDeep Learning	CodeCode Available	1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly Detection	Aug 18, 2023	Anomaly DetectionContrastive Learning	CodeCode Available	1
Camouflaged Object Detection	Jun 1, 2020	Anomaly DetectionCamouflaged Object Segmentation	CodeCode Available	1

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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