8 questions in, 58 Anny body params out. A small MLP trained with a physics-aware loss, runs in milliseconds on CPU. Height accuracy 0.3 cm, mass 0.3 kg, BWH 3-4 cm — better than our photo pipeline on circumferences, without needing a photo. That’s the questionnaire path I promised in the previous post.
The whole story begins with one observation: that height and weight can estimate body measurements quite accurately (Bartol’s regression). The original idea isn’t as accurate as it claims, but after a bit of tuning the results are quite promising.
Everyone in computer vision uses SMPL for human body reconstruction. There is one problem: SMPL has a non-commercial license that blocks production use, unless you pay a lot. For us — a tiny, two-person startup — it was out of reach.
Instead we built a fully commercial pipeline using Naver’s Anny and Meta’s MHR — both with permissive licenses. Both appeared in November 2025. The whole pipeline is cheap enough to become consumer-grade — and by consumer-grade I mean not just cost, but also time and UX. A normal person shouldn’t need instructions, a special photo, or more than a minute. Did we solve the holy grail of fashion? Here is how it works, what it costs, and where it breaks down.