Social-STAGE: Spatio-Temporal Multi-Modal Future Trajectory Forecast
Srikanth Malla, Chiho Choi, Behzad Dariush
Abstract
This paper considers the problem of multi-modal future trajectory forecast with ranking. Here, multi-modality and ranking refer to the multiple plausible path predictions and the confidence in those predictions, respectively. We propose Social-STAGE, Social interaction-aware Spatio-Temporal multi-Attention Graph convolution network with novel Evaluation for multi-modality. Our main contributions include analysis and formulation of multi-modality with ranking using interaction and multi-attention, and introduction of new metrics to evaluate the diversity and associated confidence of multi-modal predictions. We evaluate our approach on existing public datasets ETH and UCY and show that the proposed algorithm outperforms the state of the arts on these datasets.
BibTeX
@inproceedings{icra2021_socialstagespati,
title = {Social-STAGE: Spatio-Temporal Multi-Modal Future Trajectory Forecast},
author = {Srikanth Malla and Chiho Choi and Behzad Dariush},
booktitle = {ICRA 2021},
year = {2021}
}