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 281–290 of 4856 papers

Title	Date	Tasks	Status	Hype
Incomplete Multimodal Industrial Anomaly Detection via Cross-Modal Distillation	May 22, 2024	Anomaly DetectionDefect Detection	CodeCode Available	1
Spatial-aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical Image	May 21, 2024	Anomaly DetectionGenerative Adversarial Network	CodeCode Available	1
PATE: Proximity-Aware Time series anomaly Evaluation	May 20, 2024	Anomaly DetectionDecision Making	CodeCode Available	1
Position-Guided Prompt Learning for Anomaly Detection in Chest X-Rays	May 20, 2024	Anomaly DetectionPosition	CodeCode Available	1
SimAD: A Simple Dissimilarity-based Approach for Time Series Anomaly Detection	May 18, 2024	Anomaly DetectionTime Series	CodeCode Available	1
Networking Systems for Video Anomaly Detection: A Tutorial and Survey	May 16, 2024	Anomaly DetectionEdge-computing	CodeCode Available	1
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models	May 13, 2024	Anomaly DetectionEdge Detection	CodeCode Available	1
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving	May 13, 2024	Anomaly DetectionAutonomous Driving	CodeCode Available	1
MRISegmentator-Abdomen: A Fully Automated Multi-Organ and Structure Segmentation Tool for T1-weighted Abdominal MRI	May 9, 2024	Anomaly Detection	CodeCode Available	1
Supervised Anomaly Detection for Complex Industrial Images	May 8, 2024	Anomaly DetectionSupervised Anomaly Detection	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