mlsanityData to 14 Oct 2026

Face-to-BMI: Using Computer Vision to Infer Body Mass Index on Social Media

arXiv 1703.03156 ↗First posted 9 Mar 2017cs.HC cs.CV cs.CYcited by 9

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Abstract (arXiv)

A person's weight status can have profound implications on their life, ranging from mental health, to longevity, to financial income. At the societal level, "fat shaming" and other forms of "sizeism" are a growing concern, while increasing obesity rates are linked to ever raising healthcare costs. For these reasons, researchers from a variety of backgrounds are interested in studying obesity from all angles. To obtain data, traditionally, a person would have to accurately self-report their body-mass index (BMI) or would have to see a doctor to have it measured. In this paper, we show how computer vision can be used to infer a person's BMI from social media images. We hope that our tool, which we release, helps to advance the study of social aspects related to body weight.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Mar 2017.

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Citing papers per year: 2021: 4; 2022: 2; 2023: 1; 2024: 1; 2025: 0; 2026: 1.

9 papers.