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Alignment-Free Gender Recognition in the Wild

2013
Gender is possibly the most common facial attribute automatically estimated from images. Achieving robust gender classification “in the wild,” i.e. in images acquired in real settings, is still an open problem. Face pose variations are a major source of classification errors. They are solved using sophisticated face alignment algorithms that are costly
Juan Bekios-Calfa   +2 more
openaire   +2 more sources

The Misgendering Machines

Proceedings of the ACM on Human-Computer Interaction, 2018
Os Keyes
exaly  

Gender recognition: A multiscale decision fusion approach

Pattern Recognition Letters, 2010
Luis Alexandre
exaly  

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