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 2331–2340 of 4856 papers

Title	Date	Tasks	Status
Accurate and fast anomaly detection in industrial processes and IoT environments	Apr 27, 2024	Anomaly DetectionFeature Importance	—Unverified
CL-CaGAN: Capsule differential adversarial continuous learning for cross-domain hyperspectral anomaly detection	May 17, 2025	Anomaly DetectionContinual Learning	—Unverified
CL-BioGAN: Biologically-Inspired Cross-Domain Continual Learning for Hyperspectral Anomaly Detection	May 17, 2025	Anomaly DetectionContinual Learning	—Unverified
Anomaly Detection in Video Data Based on Probabilistic Latent Space Models	Mar 17, 2020	Anomaly DetectionAutonomous Vehicles	—Unverified
CLAWS: Contrastive Learning with hard Attention and Weak Supervision	Dec 1, 2021	Anomaly DetectionContrastive Learning	—Unverified
CLAWS: Clustering Assisted Weakly Supervised Learning with Normalcy Suppression for Anomalous Event Detection	Nov 24, 2020	Anomaly DetectionClustering	—Unverified
Anomaly Detection in Unsupervised Surveillance Setting Using Ensemble of Multimodal Data with Adversarial Defense	Jul 17, 2020	Adversarial AttackAdversarial Defense	—Unverified
A Lightweight Yet Robust Approach to Textual Anomaly Detection	Oct 1, 2022	Anomaly Detection	—Unverified
3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI	Mar 10, 2023	Anomaly DetectionLesion Detection	—Unverified
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model	Jan 20, 2025	Anomaly DetectionOutlier 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