Trajectron++: Dynamically-Feasible Trajectory Forecasting with Heterogeneous Data

Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, Marco Pavone

Research output: Chapter in Book/Report/Conference proceedingConference contribution

505 Citations (Scopus)
Original languageEnglish
Title of host publicationComputer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings
EditorsAndrea Vedaldi, Horst Bischof, Thomas Brox, Jan-Michael Frahm
PublisherSpringer Science and Business Media Deutschland GmbH
Pages683-700
Number of pages18
ISBN (Print)9783030585228
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event16th European Conference on Computer Vision, ECCV 2020 - Glasgow, United Kingdom
Duration: Aug 23 2020Aug 28 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12363 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th European Conference on Computer Vision, ECCV 2020
Country/TerritoryUnited Kingdom
CityGlasgow
Period8/23/208/28/20

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

Keywords

  • Autonomous driving
  • Human-robot interaction
  • Spatiotemporal graph modeling
  • Trajectory forecasting

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Cite this

Salzmann, T., Ivanovic, B., Chakravarty, P., & Pavone, M. (2020). Trajectron++: Dynamically-Feasible Trajectory Forecasting with Heterogeneous Data. In A. Vedaldi, H. Bischof, T. Brox, & J.-M. Frahm (Eds.), Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings (pp. 683-700). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12363 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58523-5_40