Paper page - SAM 3D Body: Robust Full-Body Human Mesh Recovery

Source: https://huggingface.co/papers/2602.15989 Authors:

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Abstract

A promptable 3D human mesh recovery model using a novel parametric representation and encoder-decoder architecture achieves state-of-the-art performance with strong generalization across diverse conditions.

We introduce SAM 3D Body (3DB), a promptable model for single-image full-body3D human mesh recovery(HMR) that demonstrates state-of-the-art performance, with strong generalization and consistent accuracy in diverse in-the-wild conditions. 3DB estimates the human pose of the body, feet, and hands. It is the first model to use a newparametric mesh representation,Momentum Human Rig(MHR), which decouples skeletal structure and surface shape. 3DB employs anencoder-decoder architectureand supportsauxiliary prompts, including2D keypointsandmasks, enabling user-guided inference similar to the SAM family of models. We derive high-quality annotations from a multi-stage annotation pipeline that uses various combinations of manual keypoint annotation,differentiable optimization,multi-view geometry, anddense keypoint detection. Ourdata engineefficiently selects and processes data to ensure data diversity, collecting unusual poses and rare imaging conditions. We present a newevaluation datasetorganized by pose and appearance categories, enabling nuanced analysis of model behavior. Our experiments demonstrate superior generalization and substantial improvements over prior methods in bothqualitative user preference studiesand traditionalquantitative analysis. Both 3DB and MHR are open-source.

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