mlsanityData to 14 Oct 2026

Exploring a Makeup Support System for Transgender Passing based on Automatic Gender Recognition

arXiv 2103.04544 ↗First posted 8 Mar 2021cs.HC cs.CVcited by 2

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Abstract (arXiv)

How to handle gender with machine learning is a controversial topic. A growing critical body of research brought attention to the numerous issues transgender communities face with the adoption of current automatic gender recognition (AGR) systems. In contrast, we explore how such technologies could potentially be appropriated to support transgender practices and needs, especially in non-Western contexts like Japan. We designed a virtual makeup probe to assist transgender individuals with passing, that is to be perceived as the gender they identify as. To understand how such an application might support expressing transgender individuals gender identity or not, we interviewed 15 individuals in Tokyo and found that in the right context and under strict conditions, AGR based systems could assist transgender passing.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 4 of its 41 references that are in the map. First posted on arXiv 8 Mar 2021.

Builds on

4 of 41 references.

References · 4

  1. 2017Age Progression/Regression by Conditional Adversarial Autoencodercited by 429
  2. 2019Mitigating Gender Bias in Natural Language Processing: Literature Reviewcited by 287
  3. 2019Diversity in Facescited by 77
  4. 2017On Face Segmentation, Face Swapping, and Face Perceptioncited by 71

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Cited by year

Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 0; 2025: 1.

2 papers.