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Intellindust/
SKEL_CF_vitpose_H

Name: SKEL_CF_vitpose_H
Availability: InStock

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SKEL-CF: Coarse-to-Fine Biomechanical Skeleton and Surface Mesh Recovery

TL;DR: SKEL-CF is a coarse-to-fine transformer framework for estimating anatomically accurate SKEL parameters from 3D human data. By converting 4DHuman to SKEL-aligned 4DHuman-SKEL and incorporating camera modeling, it addresses data scarcity and depth/scale ambiguities. SKEL-CF outperforms prior SKEL-based methods on MOYO (85.0 MPJPE / 51.4 PA-MPJPE), offering a scalable, biomechanically faithful solution for human motion analysis.

Model Sources

Repository: Intellindust-AI-Lab/SKEL-CF
Paper (Hugging Face): SKEL-CF: Coarse-to-Fine Biomechanical Skeleton and Surface Mesh Recovery
Paper (arXiv): SKEL-CF: Coarse-to-Fine Biomechanical Skeleton and Surface Mesh Recovery
Project Page: SKEL-CF Project Page
Demo: Github Demo

🗓️ Updates

[2025.11.26] Release SKEL-CF.
[2025.11.27] Release checkpoints and labels on Hugging Face.

⚒️ Setup

🚀 Quick Start

Quick start with images:

bash vis/run_demo.sh

Quick start with videos:

bash vis/run_video.sh

🧱 Reproducibility

For reproducing the results in the paper, please refer to docs/EVAL.md and docs/TRAIN.md.

👀 Visual Results

Per-Layer Refinement

Sports Video

Badminton Video

Skate Video

💡 Tip: Click the buttons above to watch videos, or visit our project page for more visual results.

📝 Citation

If you use SKEL-CF or its methods in your work, please cite the following BibTeX entries:

latex

@article{li2025skelcf,
  title={SKEL-CF: Coarse-to-Fine Biomechanical Skeleton and Surface Mesh Recovery},
  author={Li, Da and Jin, Jiping and Yu, Xuanlong and Cun, Xiaodong and Chen, Kai and Fan, Rui and Kong, Jiangang and Shen, Xi},
  journal={arXiv},
  year={2025}
}

📜 Acknowledgement

Parts of the code are adapted from the following repos: SKEL, CameraHMR, HSMR, ViTPose, Detectron2

Intellindust/SKEL_CF_vitpose_H