[ECCV2022] The source codes of 'Skeleton-parted graph scattering networks for 3D human motion prediction'. ECCV 2022
Python 3.6
Pytorch 0.3.1.
progress 1.5
python3 main_3d.py --data_dir "[Path To Your H36M data]/h3.6m/dataset/" --input_n 10 --output_n 10 --dct_n 15 --exp [where to save the log file]
python main_cmu_3d.py --data_dir_cmu "[Path To Your CMU data]/cmu_mocap/" --input_n 10 --output_n 25 --dct_n 30 --exp [where to save the log file]
python main_3dpw_3d.py --data_dir_3dpw "[Path To Your 3DPW data]/3DPW/sequenceFiles/" --input_n 10 --output_n 30 --dct_n 35 --exp [where to save the log file]
If you use our code, please cite our work
@inproceedings{li2022Skeleton, title={Skeleton-parted graph scattering networks for 3D human motion prediction}, author={Li, Maosen and Chen, Siheng and Zhang, Zijing and Xie, Lingxi and Tian, Qi and Zhang, Ya}, booktitle={ECCV}, year={2022} }
This readme file is going to be further updated.