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 1576–1600 of 4856 papers

Title	Date	Tasks	Status	Score
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation	Nov 30, 2018	Anomaly DetectionAutonomous Driving	CodeCode Available	5
Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining Tasks	Jul 2, 2024	Activity PredictionAnomaly Detection	CodeCode Available	5
Can I trust my anomaly detection system? A case study based on explainable AI	Jul 29, 2024	Anomaly Detection	CodeCode Available	5
Ensembled Cold-Diffusion Restorations for Unsupervised Anomaly Detection	Jul 9, 2024	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	5
Enhancing Wrist Fracture Detection with YOLO	Jul 17, 2024	Anomaly DetectionFracture detection	CodeCode Available	5
Ensemble Clustering for Graphs: Comparisons and Applications	Mar 19, 2019	Anomaly DetectionClustering	CodeCode Available	5
Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offs	Mar 12, 2024	Airbubbles DetectionAnomaly Detection	CodeCode Available	5
Enhancing Time Series Forecasting with Fuzzy Attention-Integrated Transformers	Mar 31, 2025	Anomaly DetectionDecision Making	CodeCode Available	5
Enhancing Unsupervised Anomaly Detection with Score-Guided Network	Sep 10, 2021	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	5
Anomaly Detection in Large-Scale Cloud Systems: An Industry Case and Dataset	Nov 13, 2024	Anomaly DetectionBenchmarking	CodeCode Available	5
Enhancing Robustness of On-line Learning Models on Highly Noisy Data	Mar 19, 2021	Anomaly DetectionFace Recognition	CodeCode Available	5
Enhancing Visual Perception in Novel Environments via Incremental Data Augmentation Based on Style Transfer	Sep 16, 2023	Anomaly DetectionData Augmentation	CodeCode Available	5
Evaluating Vision Transformer Models for Visual Quality Control in Industrial Manufacturing	Nov 22, 2024	Anomaly Detection	CodeCode Available	5
PyScrew: A Comprehensive Dataset Collection from Industrial Screw Driving Experiments	May 17, 2025	Anomaly DetectionFriction	CodeCode Available	5
Enhanced anomaly detection in well log data through the application of ensemble GANs	Nov 29, 2024	Anomaly Detection	CodeCode Available	5
TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly Detection	Apr 3, 2024	Anomaly DetectionData Augmentation	CodeCode Available	5
Quantum-probabilistic Hamiltonian learning for generative modelling & anomaly detection	Nov 7, 2022	Anomaly DetectionState Estimation	CodeCode Available	5
Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of Augmentation	Jun 15, 2024	Anomaly DetectionOut-of-Distribution Generalization	CodeCode Available	5
CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning	Oct 4, 2022	Anomaly DetectionContrastive Learning	CodeCode Available	5
Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-AD	Apr 29, 2024	Anomaly Detection	CodeCode Available	5
ENCODE: Encoding NetFlows for Network Anomaly Detection	Jul 8, 2022	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	5
Adaptive Deviation Learning for Visual Anomaly Detection with Data Contamination	Nov 14, 2024	Anomaly Detection	CodeCode Available	5
Eloss in the way: A Sensitive Input Quality Metrics for Intelligent Driving	Feb 2, 2023	3D Object DetectionAnomaly Detection	CodeCode Available	5
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement	Jun 3, 2024	Anomaly DetectionDecision Making	CodeCode Available	5
Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation	Apr 12, 2021	Anomaly DetectionCardiac Segmentation	CodeCode Available	5

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