# Racial Bias in the Beautyverse

arXiv: https://arxiv.org/abs/2209.13939 · HTML: https://mlsanity.com/paper/2209.13939/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 25 references that are in the map.
- First posted on arXiv 28 Sep 2022.

## Builds on (most cited first, 3 of 3)

- [Grad-CAM: Why did you say that?](https://mlsanity.com/paper/1611.07450/) (2016)
- [All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda](https://mlsanity.com/paper/2110.05352/) (2021)
- [OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters](https://mlsanity.com/paper/2207.12319/) (2022)

## Built on by (most cited first, 1 of 1)

- [A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis](https://mlsanity.com/paper/2210.04491/) (2022)

## Abstract (arXiv)

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.