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PointHPS

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Input point clouds are from HuMMan-Point (Coming Soon).

BibTex

@article{cai2023pointhps,
    title   =   {PointHPS: Cascaded 3D Human Pose and Shape Estimation from Point Clouds},
    author  =   {Cai, Zhongang and Pan, Liang, and Wei, Chen and Yin, Wanqi, and Hong, Fangzhou and Zhang, Mingyuan and Loy, Chen Change, and Yang, Lei, and Liu, Ziwei},
    year    =   {2023},
    journal =   {arXiv preprint arXiv:2308.14492}
  }

Explore More SMPLCap Projects

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  • [ECCV'24] WHAC: World-grounded human pose and camera estimation from monocular videos.
  • [CVPR'24] AiOS: An all-in-one-stage pipeline combining detection and 3D human reconstruction.
  • [NeurIPS'23] SMPLer-X: Scaling up EHPS towards a family of generalist foundation models.
  • [NeurIPS'23] RoboSMPLX: A framework to enhance the robustness of whole-body pose and shape estimation.
  • [ICCV'23] Zolly: 3D human mesh reconstruction from perspective-distorted images.
  • [arXiv'23] PointHPS: 3D HPS from point clouds captured in real-world settings.
  • [NeurIPS'22] HMR-Benchmarks: A comprehensive benchmark of HPS datasets, backbones, and training strategies.

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