Latent Terrain Representations for Trajectory Prediction-Reference-Cited by-同舟云学术

Latent Terrain Representations for Trajectory Prediction

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data - MOVE'19
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Author:

Feng Andrew¹,Gordon Andrew S.¹

Affiliation:

1. Institute for Creative Technologies, University of Southern California, Los Angeles, California

Publisher

ACM Press

Reference15 articles.

1. Alexandre Alahi, Kratarth Goel, Vignesh Ramanathan, Alexandre Robicquet, Li Fei-Fei, and Silvio Savarese. 2016. Social LSTM: Human Trajectory Prediction in Crowded Spaces. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

2. Shaojie Bai, J Zico Kolter, and Vladlen Koltun. 2018. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271 (2018).

3. Move Bank. 2017. A Free, Online Database of Animal Tracking Data. https://www.movebank.org/.

4. MILES Data. 2019. Multiple integrated laser engagement system. https://en.wikipedia.org/wiki/Multiple_integrated_laser_engagement_system.

5. Hendrik Edelhoff, Johannes Signer, and Niko Balkenhol. 2016. Path segmentation for beginners: an overview of current methods for detecting changes in animal movement patterns. Movement Ecologyvolume 4 (2016).

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1. The 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data (MOVE++ 2019);SIGSPATIAL Special;2020-02-13