Anomaly Detection on One-class CIFAR-100

Metric: AUROC (higher is better)

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#	Model↕	AUROC▼	Augmentations	Paper	Date↕	Code
1	GeneralAD	98.4	No	GeneralAD: Anomaly Detection Across Domains by A...	2024-07-17	Code
2	Transformaly	97.7	Yes	Transformaly -- Two (Feature Spaces) Are Better ...	2021-12-08	Code
3	PANDA-OE	97.3	Yes	PANDA: Adapting Pretrained Features for Anomaly ...	2020-10-12	Code
4	Mean-Shifted Contrastive Loss	96.5	Yes	Mean-Shifted Contrastive Loss for Anomaly Detect...	2021-06-07	Code
5	PANDA	94.1	Yes	PANDA: Adapting Pretrained Features for Anomaly ...	2020-10-12	Code
6	CSI	89.6	No	CSI: Novelty Detection via Contrastive Learning ...	2020-07-16	Code
7	GAN based Anomaly Detection in Imbalance Problems	87.4	No	-	-	-
8	DisAug CLR	86.5	No	Learning and Evaluating Representations for Deep...	2020-11-04	Code
9	DUIAD	86	No	Deep Unsupervised Image Anomaly Detection: An In...	2020-12-09	-
10	Rotation Prediction	84.1	No	Learning and Evaluating Representations for Deep...	2020-11-04	Code
11	MTL	83.95	No	Shifting Transformation Learning for Out-of-Dist...	2021-06-07	-
12	Self-Supervised Multi-Head RotNet	80.1	No	PANDA: Adapting Pretrained Features for Anomaly ...	2020-10-12	Code
13	Geom	78.7	No	Deep Anomaly Detection Using Geometric Transform...	2018-05-28	Code
14	Self-Supervised DeepSVDD	67	No	PANDA: Adapting Pretrained Features for Anomaly ...	2020-10-12	Code
15	Self-Supervised One-class SVM, RBF kernel	62.6	No	PANDA: Adapting Pretrained Features for Anomaly ...	2020-10-12	Code