Generative Trajectory Prediction

Generative Trajectory Prediction is a trajectory prediction approach that belongs to the class of generative models by explicitly modeling the underlying probability distribution of future trajectories to capture multimodal predictions through latent variable representations.

99

Publications

3.8K

Citations

362

Authors

139

Institutions

Publications per year

2017–2026

97

Authors

362

  1. BI
    Boris Ivanovic

    Nvidia (United Kingdom), United Kingdom

    3 publications · 178 citations

    3

    h-index

  2. HL
    Hongbo Liu

    Dalian Maritime University, China

    3 publications · 71 citations

    3

    h-index

  3. MP
    Marco Pavone

    Stanford University, United States

    3 publications · 178 citations

    3

    h-index

  4. HS
    Hyukju Shon

    Hanyang University, South Korea

    1 publications · 21 citations

    2

    h-index

  5. CJ
    Chengfeng Jia

    Wuhan University of Technology, China

    2 publications · 65 citations

    2

    h-index

1–5 of 362

Venues

  1. arXiv (Cornell University)

    Repository · 16 publications · 597 citations

    13

    h-index

  2. 5

    h-index

  3. IEEE Access

    4 publications · 106 citations

    4

    h-index

  4. 3

    h-index

  5. Ocean Engineering

    2 publications · 182 citations

    3

    h-index

1–5