@inproceedings{d6d01dc05a1c4136837e97e888041ab7,
title = "A Spatial-Temporal Graph Convolutional Networks-based Approach for the OpenPack Challenge 2022",
abstract = "We report the proposed method of Team Ritsumei for the OpenPack challenge 2022. In this work, we proposed to use a motion-aware and temporal-enhanced Spatial-Temporal Graph Convolutional Networks for the representation of the keypoint modality features. We also leverage the Accelerometer and Gyroscope modality as auxiliary modalities to improve the performance. Our final result is based on the fusion of four modalities. We report the 92.32\% F1 score on the submission set, which won the 3rd place in the OpenPack challenge 2022.",
keywords = "Action segmentation, OpenPack challenge, Spatial-Temporal Graph Convolutional Networks",
author = "Shurong Chai and Jiaqing Liu and Jain, \{Rahul Kumar\} and Yinhao Li and Tomoko Tateyama and Chen, \{Yen Wei\}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 21st IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023 ; Conference date: 13-03-2023 Through 17-03-2023",
year = "2023",
doi = "10.1109/PerComWorkshops56833.2023.10150404",
language = "English",
series = "2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "267--269",
booktitle = "Proceedings - 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023",
address = "United States",
}