Xu He¹ · Xiaoyu Li² · Di Kang² · Jiangnan Ye¹ · Chaopeng Zhang² · Liyang Chen¹ ·
Xiangjun Gao³ · Han Zhang⁴ · Zhiyong Wu^1,5 · Haolin Zhuang¹ ·
¹Tsinghua University     ²Tencent AI Lab     ³The Hong Kong University of Science and Technology
⁴Standford University     ⁵The Chinese University of Hong Kong

This repository will contain the official implementation of MagicMan. For more visual results, please checkout our project page.

|--- ckpt/
|    |--- pretrained_weights/
|    |--- magic_base/ or magic_plus/

git clone https://github.com/thuhcsi/MagicMan.git
cd MagicMan

# Create conda environment
conda create -n magicman python=3.10
conda activate magicman
# Install PyTorch and other dependencies
pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2
pip install -r requirements.txt
# Install PyTorch3D
pip install "git+https://github.com/facebookresearch/pytorch3d.git"
# Install mmcv-full
pip install "mmcv-full>=1.3.17,<1.6.0" -f https://download.openmmlab.com/mmcv/dist/cu117/torch2.0.1/index.html
# Install mmhuman3d
pip install "git+https://github.com/open-mmlab/mmhuman3d.git"

cd ./thirdparties/econ
bash fetch_data.sh

@inproceedings{SMPL-X:2019,
  title = {Expressive Body Capture: 3D Hands, Face, and Body from a Single Image},
  author = {Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.},
  booktitle = {Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019}
}
@inproceedings{PIXIE:2021,
      title={Collaborative Regression of Expressive Bodies using Moderation},
      author={Yao Feng and Vasileios Choutas and Timo Bolkart and Dimitrios Tzionas and Michael J. Black},
      booktitle={International Conference on 3D Vision (3DV)},
      year={2021}
}
@article{pymafx2023,
  title={PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular Images},
  author={Zhang, Hongwen and Tian, Yating and Zhang, Yuxiang and Li, Mengcheng and An, Liang and Sun, Zhenan and Liu, Yebin},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2023}
}
@inproceedings{pymaf2021,
  title={PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop},
  author={Zhang, Hongwen and Tian, Yating and Zhou, Xinchi and Ouyang, Wanli and Liu, Yebin and Wang, Limin and Sun, Zhenan},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
  year={2021}
}
@inproceedings{xiu2023econ,
  title     = {{ECON: Explicit Clothed humans Optimized via Normal integration}},
  author    = {Xiu, Yuliang and Yang, Jinlong and Cao, Xu and Tzionas, Dimitrios and Black, Michael J.},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  month     = {June},
  year      = {2023},
}

python inference.py --config configs/inference/inference-{version}.yaml --input_path {input_image_path} --output_path {output_dir_path} --seed 42 --device cuda:0
# e.g.,
python inference.py --config configs/inference/inference-base.yaml --input_path examples/001.jpg --output_path examples/001 --seed 42 --device cuda:0

@misc{he2024magicman,
    title={MagicMan: Generative Novel View Synthesis of Humans with 3D-Aware Diffusion and Iterative Refinement},
    author={Xu He and Xiaoyu Li and Di Kang and Jiangnan Ye and Chaopeng Zhang and Liyang Chen and Xiangjun Gao and Han Zhang and Zhiyong Wu and Haolin Zhuang},
    year={2024},
    eprint={2408.14211},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}