Anomaly Detection on One-class ImageNet-30

Metric: AUROC (higher is better)

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#	Model↕	AUROC▼	Augmentations	Paper	Date↕	Code
1	BCE-Clip (OE)	99.9	Yes	Exposing Outlier Exposure: What Can Be Learned F...	2022-05-23	Code
2	CLIP (Zero Shot)	99.88	No	Exposing Outlier Exposure: What Can Be Learned F...	2022-05-23	Code
3	Binary Cross Entropy (OE)	97.7	Yes	Exposing Outlier Exposure: What Can Be Learned F...	2022-05-23	Code
4	CSI	91.6	No	CSI: Novelty Detection via Contrastive Learning ...	2020-07-16	Code
5	FCDD	91	Yes	Explainable Deep One-Class Classification	2020-07-03	Code
6	RotNet + Translation + Self-Attention + Resize	85.7	No	Using Self-Supervised Learning Can Improve Model...	2019-06-28	Code
7	RotNet + Translation + Self-Attention	84.8	Yes	Using Self-Supervised Learning Can Improve Model...	2019-06-28	Code
8	RotNet + Self-Attention	81.6	Yes	Using Self-Supervised Learning Can Improve Model...	2019-06-28	Code
9	RotNet + Translation	77.9	Yes	Using Self-Supervised Learning Can Improve Model...	2019-06-28	Code
10	RotNet	65.3	No	Using Self-Supervised Learning Can Improve Model...	2019-06-28	Code
11	Supervised (OE)	56.1	Yes	Using Self-Supervised Learning Can Improve Model...	2019-06-28	Code