Awesome
D&D
This repo contains the code of our paper:
<!-- [[`Paper`](https://openaccess.thecvf.com/content/CVPR2021/html/Li_HybrIK_A_Hybrid_Analytical-Neural_Inverse_Kinematics_Solution_for_3D_Human_CVPR_2021_paper.html)] [[`Supplementary Material`](https://openaccess.thecvf.com/content/CVPR2021/supplemental/Li_HybrIK_A_Hybrid_CVPR_2021_supplemental.zip)] [[`arXiv`](https://arxiv.org/abs/2011.14672)] [[`Project Page`](https://jeffli.site/HybrIK/)] -->D&D: Learning Human Dynamics from Dynamic Camera
Jiefeng Li, Siyuan Bian, Chao Xu, Gang Liu, Gang Yu, Cewu Lu
ECCV 2022 Oral
Train from scratch
python ./scripts/train.py --exp-id ${EXPID} --cfg ${CONFIG} --gpu ${GPU} --seed 1
Evaluation
python ./scripts/validate.py --cfg ${CONFIG} --ckpt ${CKPT} --gpu ${GPU}
Citing
If you find our code or paper useful, please consider citing
@inproceedings{li2022dnd,
title={D\&D: Learning Human Dynamics from Dynamic Camera},
author={Li, Jiefeng and Bian, Siyuan and Xu, Chao and Liu, Gang and Yu, Gang and Lu, Cewu},
booktitle={European Conference on Computer Vision},
year={2022}
}