Abstract
This short paper proposes a preliminary and yet insightful investigation of racial biases in beauty filters techniques currently used on social media. The obtained results are a call to action for researchers in Computer Vision: such biases risk being replicated and exaggerated in the Metaverse and, as a consequence, they deserve more attention from the community.
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Acknowledgements
P.R. and N.O. are supported by a nominal grant received at the ELLIS Unit Alicante Foundation from the Regional Government of Valencia in Spain (Convenio Singular signed with Generalitat Valenciana, Conselleria d’Innovació, Universitats, Ciència i Societat Digital, Dirección General para el Avance de la Sociedad Digital). P.R. is also supported by a grant by the Banc Sabadell Foundation.
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Riccio, P., Oliver, N. (2023). Racial Bias in the Beautyverse: Evaluation of Augmented-Reality Beauty Filters. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds) Computer Vision – ECCV 2022 Workshops. ECCV 2022. Lecture Notes in Computer Science, vol 13803. Springer, Cham. https://doi.org/10.1007/978-3-031-25066-8_43
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DOI: https://doi.org/10.1007/978-3-031-25066-8_43
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