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 3941–3950 of 4856 papers

Title	Date	Tasks	Status
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation	Jul 16, 2020	Anomaly Detection	—Unverified
P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection	Jul 14, 2020	Anomaly DetectionDecoder	—Unverified
ADSAGE: Anomaly Detection in Sequences of Attributed Graph Edges applied to insider threat detection at fine-grained level	Jul 14, 2020	Anomaly DetectionFeature Engineering	—Unverified
ID-Conditioned Auto-Encoder for Unsupervised Anomaly Detection	Jul 10, 2020	Anomaly DetectionOpen Set Learning	—Unverified
Artificial Intelligence and Machine Learning in 5G Network Security: Opportunities, advantages, and future research trends	Jul 9, 2020	Anomaly DetectionBIG-bench Machine Learning	—Unverified
Learning Retrospective Knowledge with Reverse Reinforcement Learning	Jul 9, 2020	Anomaly Detectionreinforcement-learning	—Unverified
Brain Tumor Anomaly Detection via Latent Regularized Adversarial Network	Jul 9, 2020	Anomaly DetectionSemi-supervised Anomaly Detection	—Unverified
Meta-Learning for One-Class Classification with Few Examples using Order-Equivariant Network	Jul 8, 2020	Anomaly DetectionAstronomy	CodeCode Available
Deep Learning for Anomaly Detection: A Review	Jul 6, 2020	Anomaly DetectionDeep Learning	—Unverified
Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-Decoding	Jul 3, 2020	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available

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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	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	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	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	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