# Sex and Gender in the Computer Graphics Research Literature

arXiv: https://arxiv.org/abs/2206.00480 · HTML: https://mlsanity.com/paper/2206.00480/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jun 2022.

## Built on by (most cited first, 3 of 3)

- [How Will It Drape Like? Capturing Fabric Mechanics from Depth Images](https://mlsanity.com/paper/2304.06704/) (2023)
- [Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers](https://mlsanity.com/paper/2302.08572/) (2023)
- [Hairmony: Fairness-aware hairstyle classification](https://mlsanity.com/paper/2410.11528/) (2024)

## 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.