Sex and Gender in the Computer Graphics Research Literature
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Abstract (arXiv)
We survey the treatment of sex and gender in the Computer Graphics research literature from an algorithmic fairness perspective. The established practices on the use of gender and sex in our community are scientifically incorrect and constitute a form of algorithmic bias with potential harmful effects. We propose ways of addressing these as technical limitations.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Jun 2022.
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Citing papers per year: 2023: 2; 2024: 1.
3 papers.