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 1001–1010 of 4856 papers

Title	Date	Tasks	Status	Score
KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly Detection	Mar 16, 2025	Anomaly DetectionModel Selection	CodeCode Available	5
Making Anomalies More Anomalous: Video Anomaly Detection Using a Novel Generator and Destroyer	Feb 26, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	5
Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning	Jul 24, 2024	Anomaly DetectionIn-Context Learning	CodeCode Available	5
Learning Temporal Regularity in Video Sequences	Apr 15, 2016	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	5
Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series	Dec 21, 2022	Anomaly DetectionTime Series	CodeCode Available	5
IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain	Jun 12, 2025	Anomaly Detection	CodeCode Available	5
Is AUC the best measure for practical comparison of anomaly detectors?	May 8, 2023	Anomaly Detection	CodeCode Available	5
Inverting Adversarially Robust Networks for Image Synthesis	Jun 13, 2021	Anomaly DetectionDeep Feature Inversion	CodeCode Available	5
Isconna: Streaming Anomaly Detection with Frequency and Patterns	Apr 4, 2021	Anomaly Detection	CodeCode Available	5
Joint Selective State Space Model and Detrending for Robust Time Series Anomaly Detection	May 30, 2024	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