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 271–280 of 4856 papers

Title	Date	Tasks	Status	Hype
VideoVista: A Versatile Benchmark for Video Understanding and Reasoning	Jun 17, 2024	Anomaly DetectionLogical Reasoning	CodeCode Available	1
Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided Mask	Jun 16, 2024	Anomaly Detection	CodeCode Available	1
VANE-Bench: Video Anomaly Evaluation Benchmark for Conversational LMMs	Jun 14, 2024	Anomaly DetectionBenchmarking	CodeCode Available	1
Few-Shot Anomaly Detection via Category-Agnostic Registration Learning	Jun 13, 2024	Anomaly DetectionRepresentation Learning	CodeCode Available	1
Cross-Modal Learning for Anomaly Detection in Complex Industrial Process: Methodology and Benchmark	Jun 13, 2024	Anomaly DetectionARC	CodeCode Available	1
RAD: A Comprehensive Dataset for Benchmarking the Robustness of Image Anomaly Detection	Jun 11, 2024	Anomaly DetectionBenchmarking	CodeCode Available	1
LogiCode: an LLM-Driven Framework for Logical Anomaly Detection	Jun 7, 2024	Anomaly DetectionBinary Classification	CodeCode Available	1
Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations	May 30, 2024	Anomaly DetectionRepresentation Learning	CodeCode Available	1
Learning-Based Link Anomaly Detection in Continuous-Time Dynamic Graphs	May 28, 2024	Anomaly DetectionGraph Learning	CodeCode Available	1
ARC: A Generalist Graph Anomaly Detector with In-Context Learning	May 27, 2024	Anomaly DetectionARC	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