Published September 30, 2023 | Version v3.0

Semantic-Discrepant Outliers on CIFAR-10 Dataset

Authors/Creators

Description

We provide synthetic Out-of-distibution (OOD) dataset, which is called Semantic-Discrepant (SD) outliers, on CIFAR-10 dataset. SD outliers can be utilized for boosting OOD detection model performance. For the details, SD outliers are realistic OOD samples that contains incoherent semantic shift while preserving nuisances with in-distribution (ID). SD-outliers are generated from ID training samples using semantic-discrepant sampling in the diffusion model.  so SD-outliers on CIFAR-10 contains 50000 32X32 images which is same as CIFAR-10 training dataset size. The dataset has a capacity of 768MB.

Files

Files (768.0 MB)

Name Size
md5:cde4d53cf77d8d77c5e0846366d559ad
153.6 MB Download
md5:6057e1cfc4ae089f99c8c1078434dab0
153.6 MB Download
md5:bfeb26df7894989641a596cf8b332cba
153.6 MB Download
md5:e73b174e49c7cc3525ff58797b85c4cd
153.6 MB Download
md5:fbca45e7a3af2ccaa26c6c37cd177f8c
153.6 MB Download