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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Semantic-Discrepant Outliers on CIFAR-10 Dataset

Authors: Yoon, Suhee; Yoon, Sanghyu;

Semantic-Discrepant Outliers on CIFAR-10 Dataset

Abstract

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.

Keywords

Outlier, OOD generation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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