ML Anthology

Demo: Learning to Perceive Long-Range Obstacles Using Self-Supervision from Short-Range Sensors

Mirko Nava, Jérôme Guzzi, R. Omar Chavez-Garcia, Luca Maria Gambardella, Alessandro Giusti
AAAI 2019 pp. 9867-9868
doi:10.1609/AAAI.V33I01.33019867 /aaai/2019/nava2019aaai-demo/

Abstract

We demonstrate a self-supervised approach which learns to detect long-range obstacles from video: it automatically obtains training labels by associating the camera frames acquired at a given pose to short-range sensor readings acquired at a different pose.

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Cite

Text

Nava et al. "Demo: Learning to Perceive Long-Range Obstacles Using Self-Supervision from Short-Range Sensors." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.33019867

Markdown

[Nava et al. "Demo: Learning to Perceive Long-Range Obstacles Using Self-Supervision from Short-Range Sensors." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/nava2019aaai-demo/) doi:10.1609/AAAI.V33I01.33019867

BibTeX

@inproceedings{nava2019aaai-demo,
  title     = {{Demo: Learning to Perceive Long-Range Obstacles Using Self-Supervision from Short-Range Sensors}},
  author    = {Nava, Mirko and Guzzi, Jérôme and Chavez-Garcia, R. Omar and Gambardella, Luca Maria and Giusti, Alessandro},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2019},
  pages     = {9867-9868},
  doi       = {10.1609/AAAI.V33I01.33019867},
  url       = {https://mlanthology.org/aaai/2019/nava2019aaai-demo/}
}