[CVPR-2024] A Dual Augmentor Framework for Domain Generalization in 3D Human Pose Estimation

Prerequisites:

• Datasets: Please follow PoseAug and AdaptPose.
• Environments: Please follow PoseAug.
• Backbone: Here we only provide the VideoPose3D as the 2D-lifting-3D backbone. You can try other backbones by adding new directories in "model_baseline"
• Pretraining and Evaluation: We do not contain these parts in the repo. You can either follow previous works like PoseAug and AdaptPose to implement or write it by yourself.

Run Training Codes:

python3 run_daf_dg.py --note poseaug --posenet_name 'videopose' --checkpoint './checkpoint' --keypoints gt

Citation

If you find this code useful for your research, please cite our paper

@article{peng2024dual,
  title={A Dual-Augmentor Framework for Domain Generalization in 3D Human Pose Estimation},
  author={Peng, Qucheng and Zheng, Ce and Chen, Chen},
  journal={arXiv preprint arXiv:2403.11310},
  year={2024}
}

Acknowledge

Borrow a lot from PoseAug.