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 561–570 of 4856 papers

Title	Date	Tasks	Status	Hype
Revisiting Multimodal Fusion for 3D Anomaly Detection from an Architectural Perspective	Dec 23, 2024	3D Anomaly DetectionAnomaly Detection	CodeCode Available	0
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection	Dec 23, 2024	Anomaly DetectionPrompt Learning	CodeCode Available	1
VarAD: Lightweight High-Resolution Image Anomaly Detection via Visual Autoregressive Modeling	Dec 23, 2024	Anomaly DetectionMamba	CodeCode Available	1
Dual Conditioned Motion Diffusion for Pose-Based Video Anomaly Detection	Dec 23, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	2
Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection	Dec 23, 2024	Anomaly DetectionBinary Classification	CodeCode Available	1
A Parameter-Efficient Quantum Anomaly Detection Method on a Superconducting Quantum Processor	Dec 22, 2024	Anomaly DetectionQuantum Machine Learning	CodeCode Available	0
A Generalizable Anomaly Detection Method in Dynamic Graphs	Dec 21, 2024	Anomaly DetectionDiversity	CodeCode Available	2
Effective and Efficient Representation Learning for Flight Trajectories	Dec 21, 2024	Anomaly DetectionRepresentation Learning	CodeCode Available	0
DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction	Dec 21, 2024	Anomaly DetectionContrastive Learning	—Unverified	0
Iterative Encoding-Decoding VAEs Anomaly Detection in NOAA's DART Time Series: A Machine Learning Approach for Enhancing Data Integrity for NASA's GRACE-FO Verification and Validation	Dec 20, 2024	Anomaly DetectionTime Series	—Unverified	0

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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