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 581–590 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy	Jun 26, 2020	Anomaly Detection	CodeCode Available	1	5
Few-Shot Anomaly Detection via Category-Agnostic Registration Learning	Jun 13, 2024	Anomaly DetectionRepresentation Learning	CodeCode Available	1	5
A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams	Apr 21, 2021	Anomaly DetectionDrift Detection	CodeCode Available	1	5
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges	Oct 26, 2021	Anomaly DetectionNovelty Detection	CodeCode Available	1	5
AUPIMO: Redefining Visual Anomaly Detection Benchmarks with High Speed and Low Tolerance	Jan 3, 2024	Anomaly Detection	CodeCode Available	1	5
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR Data	Mar 14, 2025	Anomaly DetectionDecoder	CodeCode Available	1	5
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection	Jun 15, 2021	Anomaly DetectionFederated Learning	CodeCode Available	1	5
Auto-Encoding Variational Bayes	Dec 20, 2013	Anomaly DetectionImage Clustering	CodeCode Available	1	5
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks	Dec 23, 2022	Anomaly DetectionPrivacy Preserving	CodeCode Available	1	5
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly Detection	Aug 19, 2022	Anomaly DetectionRepresentation Learning	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