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 1541–1550 of 4856 papers

Title	Date	Tasks	Status	Hype
Produce Once, Utilize Twice for Anomaly Detection	Dec 20, 2023	Anomaly Detection	—Unverified	0
When Model Meets New Normals: Test-time Adaptation for Unsupervised Time-series Anomaly Detection	Dec 19, 2023	Anomaly DetectionTest-time Adaptation	CodeCode Available	1
A Survey on IoT Ground Sensing Systems for Early Wildfire Detection: Technologies, Challenges and Opportunities	Dec 18, 2023	Anomaly Detection	—Unverified	0
Residual ANODE	Dec 18, 2023	Anomaly DetectionInductive Bias	—Unverified	0
PARs: Predicate-based Association Rules for Efficient and Accurate Model-Agnostic Anomaly Explanation	Dec 18, 2023	Anomaly Detection	CodeCode Available	0
Label-Free Multivariate Time Series Anomaly Detection	Dec 17, 2023	Anomaly DetectionDensity Estimation	CodeCode Available	1
TAB: Text-Align Anomaly Backbone Model for Industrial Inspection Tasks	Dec 15, 2023	Anomaly ClassificationAnomaly Detection	—Unverified	0
TSRNet: Simple Framework for Real-time ECG Anomaly Detection with Multimodal Time and Spectrogram Restoration Network	Dec 15, 2023	Anomaly DetectionRhythm	CodeCode Available	1
Entropy Causal Graphs for Multivariate Time Series Anomaly Detection	Dec 15, 2023	Anomaly DetectionTime Series	CodeCode Available	1
Deep Anomaly Detection in Text	Dec 14, 2023	Anomaly DetectionRepresentation Learning	—Unverified	0

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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