MHR: Momentum Human Rig
Paper β’ 2511.15586 β’ Published β’ 14
How to use peabody124/Sam3dBodyEqx with SAM 3D Body:
from notebook.utils import setup_sam_3d_body estimator = setup_sam_3d_body(peabody124/Sam3dBodyEqx) outputs = estimator.process_one_image(image) rend_img = visualize_sample_together(image, outputs, estimator.faces)
Pre-converted JAX/Equinox (.eqx) weights for Sam3dBodyEqx,
a pure JAX/Equinox port of Meta's SAM 3D Body
for single-image full-body 3D human mesh recovery. No PyTorch runtime is needed for inference.
| File | What it is | License |
|---|---|---|
sam3d_body.eqx |
Converted SAM 3D Body model (backbone + decoder + heads) | SAM License β see LICENSE.component.sam-3d-body |
mhr.eqx |
Converted Momentum Human Rig (MHR) forward-kinematics body model | Apache-2.0 β see LICENSE.component.mhr |
These are converted forms of Meta's released models; the upstream licenses are
preserved and redistributed here. The SAM License is maintained for
sam3d_body.eqx (no military/nuclear/espionage or ITAR use; redistributions
must include the license; patent litigation terminates the grant).
from sam3d_body_eqx.mhr.mhr_model import MHRForwardKinematics
mhr = MHRForwardKinematics.from_pretrained(
repo_id="peabody124/Sam3dBodyEqx", filename="mhr.eqx"
)
@article{yang2025sam3dbody,
title={SAM 3D Body: Robust Full-Body Human Mesh Recovery},
author={Yang, Xitong and Kukreja, Devansh and Pinkus, Don and others},
journal={arXiv preprint}, year={2025}
}
@misc{MHR:2025,
title={MHR: Momentum Human Rig},
author={Ferguson, Aaron and Osman, Ahmed A. A. and Bescos, Berta and others},
year={2025}, eprint={2511.15586}, archivePrefix={arXiv}, primaryClass={cs.GR}
}