Difference between revisions of "VGG-Face"
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| − | In the search for datasets sufficient to use in the training and testing of these data-hungry methods, many were inspired by Web-sourced benchmarks such as LfW, resulting in datasets such as Oxford’s VGG-Face dataset (Parkhi et al. 2015), Microsoft’s 1M MS Celeb (Guo et al. 2016), MegaFace (Kemelmacher-Shlizerman et al. 2016), and the CASIA WebFace dataset (Yi et al. 2014). [[CiteRef::rajiFaceSurveyFacial2021]] | + | <blockquote>In the search for datasets sufficient to use in the training and testing of these data-hungry methods, many were inspired by Web-sourced benchmarks such as LfW, resulting in datasets such as Oxford’s VGG-Face dataset (Parkhi et al. 2015), Microsoft’s 1M MS Celeb (Guo et al. 2016), MegaFace (Kemelmacher-Shlizerman et al. 2016), and the CASIA WebFace dataset (Yi et al. 2014). [[CiteRef::rajiFaceSurveyFacial2021]]</blockquote> |
Revision as of 19:50, 26 February 2021
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Description[edit | ]
In the search for datasets sufficient to use in the training and testing of these data-hungry methods, many were inspired by Web-sourced benchmarks such as LfW, resulting in datasets such as Oxford’s VGG-Face dataset (Parkhi et al. 2015), Microsoft’s 1M MS Celeb (Guo et al. 2016), MegaFace (Kemelmacher-Shlizerman et al. 2016), and the CASIA WebFace dataset (Yi et al. 2014). 1
References
- ^ Raji, Inioluwa Deborah and Fried, Genevieve. About Face: A Survey of Facial Recognition Evaluation. , 2021.