Quantum Motion Segmentation

Federica Arrigoni, Willi Menapace, Marcel Seelbach Benkner, Elisa Ricci, Vladislav Golyanik

ECCV 2022

doi:10.1007/978-3-031-19818-2_29 /eccv/2022/arrigoni2022eccv-quantum/

Abstract

Motion segmentation is a challenging problem that seeks to identify independent motions in two or several input images. This paper introduces the first algorithm for motion segmentation that relies on adiabatic quantum optimization of the objective function. The proposed method achieves on-par performance with the state of the art on problem instances which can be mapped to modern quantum annealers.

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Cite

Text

Arrigoni et al. "Quantum Motion Segmentation." Proceedings of the European Conference on Computer Vision (ECCV), 2022. doi:10.1007/978-3-031-19818-2_29

Markdown

[Arrigoni et al. "Quantum Motion Segmentation." Proceedings of the European Conference on Computer Vision (ECCV), 2022.](https://mlanthology.org/eccv/2022/arrigoni2022eccv-quantum/) doi:10.1007/978-3-031-19818-2_29

BibTeX

@inproceedings{arrigoni2022eccv-quantum,
  title     = {{Quantum Motion Segmentation}},
  author    = {Arrigoni, Federica and Menapace, Willi and Benkner, Marcel Seelbach and Ricci, Elisa and Golyanik, Vladislav},
  booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
  year      = {2022},
  doi       = {10.1007/978-3-031-19818-2_29},
  url       = {https://mlanthology.org/eccv/2022/arrigoni2022eccv-quantum/}
}