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 1091–1100 of 4856 papers

Title	Date	Tasks	Status	Score
Image-Pointcloud Fusion based Anomaly Detection using PD-REAL Dataset	Nov 7, 2023	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	5
Online Detection of Anomalies in Temporal Knowledge Graphs with Interpretability	Aug 1, 2024	Anomaly DetectionGraph Anomaly Detection	CodeCode Available	5
Image anomaly detection with capsule networks and imbalanced datasets	Sep 6, 2019	Anomaly Detection	CodeCode Available	5
Imbalanced Graph-Level Anomaly Detection via Counterfactual Augmentation and Feature Learning	Jul 13, 2024	Anomaly DetectionAttribute	CodeCode Available	5
Improved Anomaly Detection by Using the Attention-Based Isolation Forest	Oct 5, 2022	Anomaly Detection	CodeCode Available	5
Industrial Image Anomaly Localization Based on Gaussian Clustering of Pretrained Feature	Jan 6, 2021	Anomaly DetectionAnomaly Localization	CodeCode Available	5
Attribute Restoration Framework for Anomaly Detection	Nov 25, 2019	Anomaly DetectionAttribute	CodeCode Available	5
Hyperspectral Image Denoising and Anomaly Detection Based on Low-rank and Sparse Representations	Mar 12, 2021	Anomaly DetectionDenoising	CodeCode Available	5
Identification of Unexpected Decisions in Partially Observable Monte-Carlo Planning: a Rule-Based Approach	Dec 23, 2020	Anomaly DetectionRobot Navigation	CodeCode Available	5
HyperBrain: Anomaly Detection for Temporal Hypergraph Brain Networks	Oct 2, 2024	Anomaly DetectionGraph Learning	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	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