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 1721–1730 of 4856 papers

Title	Date	Tasks	Status
Does Your Phone Know Your Touch?	Sep 10, 2018	Anomaly DetectionPosition	—Unverified
Data Anomaly Detection for Structural Health Monitoring of Bridges using Shapelet Transform	Aug 31, 2020	Anomaly DetectionBIG-bench Machine Learning	—Unverified
Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection	Apr 15, 2024	Anomaly DetectionAnomaly Localization	—Unverified
Domain Adaptation via Anaomaly Detection	Jan 1, 2021	Anomaly DetectionDomain Adaptation	—Unverified
A Survey of Distance-Based Vessel Trajectory Clustering: Data Pre-processing, Methodologies, Applications, and Experimental Evaluation	Jul 13, 2024	Anomaly DetectionClustering	—Unverified
Domain-Generalized Textured Surface Anomaly Detection	Mar 23, 2022	Anomaly DetectionDomain Generalization	—Unverified
Data-Agnostic Face Image Synthesis Detection Using Bayesian CNNs	Jan 8, 2024	Anomaly DetectionImage Generation	—Unverified
Anomaly Locality in Video Surveillance	Jan 29, 2019	Anomaly Detection	—Unverified
Domain-Specific Retrieval-Augmented Generation Using Vector Stores, Knowledge Graphs, and Tensor Factorization	Oct 3, 2024	Anomaly DetectionAttribute	—Unverified
DAS3D: Dual-modality Anomaly Synthesis for 3D Anomaly Detection	Oct 13, 2024	3D Anomaly DetectionAnomaly Detection	—Unverified

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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