ML Anthology

Soccer on Your Tabletop

Konstantinos Rematas, Ira Kemelmacher-Shlizerman, Brian Curless, Steve Seitz
CVPR 2018
doi:10.1109/CVPR.2018.00498 /cvpr/2018/rematas2018cvpr-soccer/

Abstract

We present a system that transforms a monocular video of a soccer game into a moving 3D reconstruction, in which the players and field can be rendered interactively with a 3D viewer or through an Augmented Reality device. At the heart of our paper is an approach to estimate the depth map of each player, using a CNN that is trained on 3D player data extracted from soccer video games. We compare with state of the art body pose and depth estimation techniques, and show results on both synthetic ground truth benchmarks, and real YouTube soccer footage.

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Cite

Text

Rematas et al. "Soccer on Your Tabletop." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018. doi:10.1109/CVPR.2018.00498

Markdown

[Rematas et al. "Soccer on Your Tabletop." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018.](https://mlanthology.org/cvpr/2018/rematas2018cvpr-soccer/) doi:10.1109/CVPR.2018.00498

BibTeX

@inproceedings{rematas2018cvpr-soccer,
  title     = {{Soccer on Your Tabletop}},
  author    = {Rematas, Konstantinos and Kemelmacher-Shlizerman, Ira and Curless, Brian and Seitz, Steve},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2018},
  doi       = {10.1109/CVPR.2018.00498},
  url       = {https://mlanthology.org/cvpr/2018/rematas2018cvpr-soccer/}
}