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 1761–1770 of 4856 papers

Title	Date	Tasks	Status	Hype
Divide and Conquer in Video Anomaly Detection: A Comprehensive Review and New Approach	Sep 26, 2023	Anomaly DetectionPhilosophy	CodeCode Available	0
Sampling - Variational Auto Encoder - Ensemble: In the Quest of Explainable Artificial Intelligence	Sep 25, 2023	Anomaly DetectionExplainable artificial intelligence	—Unverified	0
Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernels	Sep 25, 2023	Anomaly DetectionComputational Efficiency	CodeCode Available	1
LogGPT: Log Anomaly Detection via GPT	Sep 25, 2023	Anomaly DetectionLanguage Modeling	CodeCode Available	1
Towards Surveillance Video-and-Language Understanding: New Dataset, Baselines, and Challenges	Sep 25, 2023	Anomaly DetectionDense Video Captioning	—Unverified	0
(Predictable) Performance Bias in Unsupervised Anomaly Detection	Sep 25, 2023	Anomaly DetectionFairness	—Unverified	0
Real3D-AD: A Dataset of Point Cloud Anomaly Detection	Sep 23, 2023	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1
NetDiffus: Network Traffic Generation by Diffusion Models through Time-Series Imaging	Sep 23, 2023	Anomaly DetectionTime Series	CodeCode Available	1
STemGAN: spatio-temporal generative adversarial network for video anomaly detection	Sep 22, 2023	Anomaly DetectionAnomaly Detection In Surveillance Videos	—Unverified	0
mixed attention auto encoder for multi-class industrial anomaly detection	Sep 22, 2023	Anomaly DetectionMulti-class Anomaly Detection	—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