code for "ICE-GCN: Interactional channel excitation enhanced graph convolutional network for skeleton-based action recognition"
Fig. 1: Schematic diagram of the ICE on the skeleton sequence of action “kicking something”
Fig. 2: Schematic comparison between the proposed CSE (c), CTE (d) and the classical attention module of SENet (a), CBAM (b).
conda env create -f ice_gcn_environment.yml
follow CTR-GCN.
This repo is based on CTR-GCN and 2s-AGCN. The data processing is borrowed from SGN and HCN.
Thanks to the original authors for their work!
Please cite this work if you find it useful:.
@article{wang2023ice,
title={ICE-GCN: An interactional channel excitation-enhanced graph convolutional network for skeleton-based action recognition},
author={Wang, Shuxi and Pan, Jiahui and Huang, Binyuan and Liu, Pingzhi and Li, Zina and Zhou, Chengju},
journal={Machine Vision and Applications},
volume={34},
number={3},
pages={40},
year={2023},
publisher={Springer}
}