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 2951–2960 of 4856 papers

Title	Date	Tasks	Status
Rethinking Video Anomaly Detection - A Continual Learning Approach	Jan 1, 2022	Anomaly DetectionContinual Learning	—Unverified
Retrieval Augmented Anomaly Detection (RAAD): Nimble Model Adjustment Without Retraining	Feb 26, 2025	Anomaly DetectionLightweight Deployment	—Unverified
Detection of Backdoors in Trained Classifiers Without Access to the Training Set	Aug 27, 2019	Anomaly DetectionData Poisoning	—Unverified
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection	Mar 15, 2023	Anomaly DetectionAnomaly Segmentation	—Unverified
Revisited Large Language Model for Time Series Analysis through Modality Alignment	Oct 16, 2024	Anomaly DetectionImputation	—Unverified
Revisiting DDIM Inversion for Controlling Defect Generation by Disentangling the Background	Nov 25, 2024	Anomaly DetectionDenoising	—Unverified
Revisiting randomized choices in isolation forests	Oct 26, 2021	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
Revitalizing Reconstruction Models for Multi-class Anomaly Detection via Class-Aware Contrastive Learning	Dec 6, 2024	Anomaly DetectionContrastive Learning	—Unverified
ReX: A Framework for Incorporating Temporal Information in Model-Agnostic Local Explanation Techniques	Sep 8, 2022	Anomaly DetectionSentiment Analysis	—Unverified
RGI: robust GAN-inversion for mask-free image inpainting and unsupervised pixel-wise anomaly detection	Feb 24, 2023	Anomaly DetectionImage Inpainting	—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	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	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	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	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