Action Anticipation By Predicting Future Dynamic Images [article]

Cristian Rodriguez, Basura Fernando, Hongdong Li
2018 arXiv   pre-print
Human action-anticipation methods predict what is the future action by observing only a few portion of an action in progress. This is critical for applications where computers have to react to human actions as early as possible such as autonomous driving, human-robotic interaction, assistive robotics among others. In this paper, we present a method for human action anticipation by predicting the most plausible future human motion. We represent human motion using Dynamic Images and make use of
more » ... ilored loss functions to encourage a generative model to produce accurate future motion prediction. Our method outperforms the currently best performing action-anticipation methods by 4% on JHMDB-21, 5.2% on UT-Interaction and 5.1% on UCF 101-24 benchmarks.
arXiv:1808.00141v1 fatcat:4rzxmxnoyfdl3lyinmm2u7ngge