Neural Localizer Fields for Continuous 3D Human Pose and Shape Estimation

• NeurIPS'24 paper by István Sárándi and Gerard Pons-Moll
• Project page

Models for PyTorch and TensorFlow are available for noncommercial research use under Releases, and usage examples are given in demo.ipynb. Stay tuned for more detailed docs.

Training code is provided for both PyTorch and TensorFlow.

Acknowledgments

This work was supported by the German Federal Ministry of Education and Research (BMBF): Tübingen AI Center, FKZ: 01IS18039A. This work is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 409792180 (Emmy Noether Programme, project: Real Virtual Humans). GPM is a member of the Machine Learning Cluster of Excellence, EXC number 2064/1 –Project number 390727645. The project was made possible by funding from the Carl Zeiss Foundation.

BibTeX

@article{sarandi2024nlf,
    title     = {Neural Localizer Fields for Continuous 3D Human Pose and Shape Estimation},
    author    = {S\'ar\'andi, Istv\'an and Pons-Moll, Gerard},
    booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
    year      = {2024}
}