SAR-NAS

Code accompanying the paper
SAR-NAS: Skeleton-based Action Recognition via Neural Architecture Searching
Accepted by the Journal of Visual Communication and Image Representation.

Requirements

Python >= 3.5.5, PyTorch == 0.4.1, torchvision == 0.2.1.

Datasets

Skeleton data in NTU RGB+D and Kinetics400.

Architecture search

python train_search_ntu.py

Architecture evaluation

python train_ntu.py

Confusion matrix

python draw_confusion_matrix.py

Visualization

Package graphviz is required to visualize the learned cells
python visualize.py DARTS
where DARTS can be replaced by any customized architectures in genotypes.py

Citation

If you use any part of this code in your research, please cite our paper:
@article{Zhang2020sar-darts,
title={SAR-NAS: Skeleton-based Action Recognition via Neural Architecture Searching},
author={Zhang, Haoyuan and Hou, Yonghong and Wang, Pichao and Guo, Zihui and Li, Wanqing},
journal={Journal of Visual Communication and Image Representation, preprint},
year={2020}
}