OOD Detection on CIFAR-10 (test) using Specialized AUROC Metrics benchmark leaderboard · SOTA2 Research

OOD Detection on CIFAR-10 (test) using Specialized AUROC Metrics

0.995Clean AUROCViT

Evaluation Results

Method	Links
ViT2022.09		0.995	0.26	0.571	0.004
ViT2022.09		0.984	0.339	0.355	0.007
ViT2022.09		0.975	0.578	0.28	0.013
OpenGAN-fea2022.09		0.971	0.521	0.444	0.318
ViT2022.09		0.951	0.526	0.493	0.043
ATD2022.09		0.943	0.915	0.919	0.883
HAT2022.09		0.878	0.74	0.764	0.573
ALOE2022.09		0.869	0.658	0.679	0.422
ALOE2022.09		0.843	0.667	0.612	0.373
AT2022.09		0.836	0.64	0.69	0.453
OSAD2022.09		0.827	0.696	0.699	0.535
ALOE2022.09		0.827	0.602	0.646	0.406
HAT2022.09		0.821	0.729	0.741	0.633
OpenGAN-pixel2022.09		0.818	0.001	0.052	0
ALOE2022.09		0.815	0.512	0.57	0.213
AT2022.09		0.805	0.647	0.669	0.489
AOE2022.09		0.797	0.675	0.702	0.559
HAT2022.09		0.789	0.691	0.688	0.579
AOE2022.09		0.78	0.658	0.654	0.514
AOE2022.09		0.78	0.562	0.595	0.337
OSAD2022.09		0.776	0.576	0.619	0.384
AT2022.09		0.771	0.603	0.65	0.473
HAT2022.09		0.77	0.665	0.658	0.541
AT2022.09		0.735	0.573	0.564	0.394
AOE2022.09		0.709	0.515	0.587	0.407
OSAD2022.09		0.698	0.521	0.516	0.347
OSAD2022.09		0.626	0.5	0.521	0.402