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 891–900 of 4856 papers

Title	Date	Tasks	Status	Hype
TAnoGAN: Time Series Anomaly Detection with Generative Adversarial Networks	Aug 21, 2020	Anomaly DetectionTime Series	CodeCode Available	1
Target before Shooting: Accurate Anomaly Detection and Localization under One Millisecond via Cascade Patch Retrieval	Aug 13, 2023	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1
TeD-SPAD: Temporal Distinctiveness for Self-supervised Privacy-preservation for video Anomaly Detection	Aug 21, 2023	Anomaly DetectionAttribute	CodeCode Available	1
BMAD: Benchmarks for Medical Anomaly Detection	Jun 20, 2023	Anomaly DetectionMedical Diagnosis	CodeCode Available	1
Anomaly Detection in Aerial Videos with Transformers	Sep 25, 2022	Anomaly Detection	CodeCode Available	1
Blind Localization and Clustering of Anomalies in Textures	Apr 18, 2024	Anomaly DetectionAnomaly Localization	CodeCode Available	1
The OPS-SAT benchmark for detecting anomalies in satellite telemetry	Jun 29, 2024	Anomaly Detection	CodeCode Available	1
The role of noise in denoising models for anomaly detection in medical images	Jan 19, 2023	Anomaly DetectionDenoising	CodeCode Available	1
Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection	Jul 25, 2022	Anomaly DetectionOne-Class Classification	CodeCode Available	1
Challenges in Visual Anomaly Detection for Mobile Robots	Sep 22, 2022	Anomaly Detection	CodeCode Available	1

Show:10 25 50

← PrevPage 90 of 486Next →

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