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 3826–3850 of 4856 papers

Title	Date	Tasks	Status	Hype
Fast Unsupervised Anomaly Detection in Traffic Videos	Jul 28, 2020	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	1
Cassandra: Detecting Trojaned Networks from Adversarial Perturbations	Jul 28, 2020	Adversarial DefenseAnomaly Detection	—Unverified	0
A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories	Jul 28, 2020	Anomaly DetectionAutonomous Driving	—Unverified	0
Anomaly detection in Context-aware Feature Models	Jul 28, 2020	Anomaly Detection	—Unverified	0
DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision	Jul 28, 2020	Anomaly Detection	CodeCode Available	1
Improving Robustness on Seasonality-Heavy Multivariate Time Series Anomaly Detection	Jul 25, 2020	Anomaly DetectionGenerative Adversarial Network	—Unverified	0
Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning	Jul 25, 2020	Anomaly DetectionFault Diagnosis	—Unverified	0
Insightful Assistant: AI-compatible Operation Graph Representations for Enhancing Industrial Conversational Agents	Jul 25, 2020	Anomaly Detection	—Unverified	0
MADGAN: unsupervised Medical Anomaly Detection GAN using multiple adjacent brain MRI slice reconstruction	Jul 24, 2020	Anomaly DetectionGenerative Adversarial Network	—Unverified	0
Improved Slice-wise Tumour Detection in Brain MRIs by Computing Dissimilarities between Latent Representations	Jul 24, 2020	Anomaly Detection	—Unverified	0
Weakly and Partially Supervised Learning Frameworks for Anomaly Detection	Jul 23, 2020	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	1
Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature Importance	Jul 21, 2020	Anomaly DetectionFeature Importance	CodeCode Available	1
Human Abnormality Detection Based on Bengali Text	Jul 21, 2020	Anomaly Detection	—Unverified	0
Anomaly Awareness	Jul 20, 2020	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
Unsupervised anomaly detection for discrete sequence healthcare data	Jul 20, 2020	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach	Jul 19, 2020	Anomaly DetectionFederated Learning	—Unverified	0
Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization	Jul 18, 2020	Anomaly DetectionDomain Generalization	—Unverified	0
DDR-ID: Dual Deep Reconstruction Networks Based Image Decomposition for Anomaly Detection	Jul 18, 2020	Adversarial AttackAdversarial Attack Detection	—Unverified	0
Few-Shot Defect Segmentation Leveraging Abundant Normal Training Samples Through Normal Background Regularization and Crop-and-Paste Operation	Jul 18, 2020	Anomaly DetectionBenchmarking	—Unverified	0
Backpropagated Gradient Representations for Anomaly Detection	Jul 18, 2020	Anomaly DetectionComputational Efficiency	CodeCode Available	1
Anomaly Detection in Unsupervised Surveillance Setting Using Ensemble of Multimodal Data with Adversarial Defense	Jul 17, 2020	Adversarial AttackAdversarial Defense	—Unverified	0
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation	Jul 16, 2020	Anomaly Detection	—Unverified	0
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances	Jul 16, 2020	Anomaly DetectionContrastive Learning	CodeCode Available	1
Few-shot Scene-adaptive Anomaly Detection	Jul 15, 2020	Anomaly DetectionMeta-Learning	CodeCode Available	1
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	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