Investigating Anthropometric Fidelity in SAM 3D Body

The paper examines the SAM 3D Body model’s difficulty in accurately capturing detailed anthropometric variations—such as those seen in geriatric muscle atrophy, scoliosis, or pregnancy—despite clear visual cues. It attributes this limitation to a perception‑distortion trade‑off arising from the model’s reliance on a low‑dimensional parametric MHR representation, semantic‑invariant conditioning, and annotation‑based alignment, which collectively cause a regression‑to‑the‑mean effect. The authors propose future directions, including hybrid representations and medical‑in‑the‑loop alignment, to enhance the model’s precision for medical applications.

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