PreTraM: Self-supervised Pre-training via Connecting Trajectory and Map

Chenfeng Xu, Tian Li, Chen Tang, Lingfeng Sun, Kurt Keutzer, Masayoshi Tomizuka, Alireza Fathi, Wei Zhan. PreTraM: Self-supervised Pre-training via Connecting Trajectory and Map. In Shai Avidan, Gabriel J. Brostow, Moustapha Cissé, Giovanni Maria Farinella, Tal Hassner, editors, Computer Vision - ECCV 2022 - 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXXIX. Volume 13699 of Lecture Notes in Computer Science, pages 34-50, Springer, 2022. [doi]

@inproceedings{XuLTSKTFZ22,
  title = {PreTraM: Self-supervised Pre-training via Connecting Trajectory and Map},
  author = {Chenfeng Xu and Tian Li and Chen Tang and Lingfeng Sun and Kurt Keutzer and Masayoshi Tomizuka and Alireza Fathi and Wei Zhan},
  year = {2022},
  doi = {10.1007/978-3-031-19842-7_3},
  url = {https://doi.org/10.1007/978-3-031-19842-7_3},
  researchr = {https://researchr.org/publication/XuLTSKTFZ22},
  cites = {0},
  citedby = {0},
  pages = {34-50},
  booktitle = {Computer Vision - ECCV 2022 - 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXXIX},
  editor = {Shai Avidan and Gabriel J. Brostow and Moustapha Cissé and Giovanni Maria Farinella and Tal Hassner},
  volume = {13699},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-031-19842-7},
}