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 751–760 of 4856 papers

Title	Date	Tasks	Status	Hype
ADNet: Temporal Anomaly Detection in Surveillance Videos	Apr 14, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting	Dec 22, 2023	Anomaly DetectionTime Series	CodeCode Available	1
CwA-T: A Channelwise AutoEncoder with Transformer for EEG Abnormality Detection	Dec 19, 2024	Anomaly DetectionEEG	CodeCode Available	1
MemStream: Memory-Based Streaming Anomaly Detection	Jun 7, 2021	Anomaly DetectionDenoising	CodeCode Available	1
Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning	Sep 16, 2020	Anomaly DetectionDeep Reinforcement Learning	CodeCode Available	1
Can Multimodal LLMs Perform Time Series Anomaly Detection?	Feb 25, 2025	Anomaly DetectionIrregular Time Series	CodeCode Available	1
An End-to-End Computer Vision Methodology for Quantitative Metallography	Apr 22, 2021	Anomaly DetectionImage Inpainting	CodeCode Available	1
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers	Oct 21, 2020	Anomaly DetectionKeyword Spotting	CodeCode Available	1
A Comprehensive Survey of Regression Based Loss Functions for Time Series Forecasting	Nov 5, 2022	Anomaly Detectionregression	CodeCode Available	1
Broiler-Net: A Deep Convolutional Framework for Broiler Behavior Analysis in Poultry Houses	Jan 22, 2024	Anomaly Detection	CodeCode Available	1

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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