This is the code for the ICCV 2025 paper "STaR: Seamless Spatial-Temporal Aware Motion Retargeting with Penetration and Consistency Constraints", by Xiaohang Yang, et al.

Neural motion retargeting model, STaR, is designed for a balance between: (1) motion semantics preservation, (2) physical plausibility, and (3) temporal consistency.

🚀 Update: The full code will be released soon—stay tuned! 👀

• test code, with network weight and a processed test set;
• inference code, with a PyTorch3D-based rendering function;
• data preparation;
• release a skel2mesh motion retargeting sub-model based on STaR, which can be used for retargeting motion generation results to new characters;

We tested with Python 3.9, CUDA 11.8.

conda create python=3.9 -n star
conda activate star

• Install PyTorch. We have tested on PyTorch 2.3.1.

conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=11.8 -c pytorch -c nvidia

• Install PyTorch3D (for visualisation only).

  Build from source code or refer to this link for pre-built wheels that matches your environments.

pip install numpy==1.23.3 tqdm wandb scipy matplotlib==3.4.2 ninja
cd ./submodules
pip install ./pointnet2_ops_lib/.

Download the processed test set from here. Put all content under ./datasets/mixamo/

python test.py --config ./config/test_config.yaml

(We use scripts to download, match motion instances and create datesets. This part is a little bit complicated, we will release this part as soon as possible, together with a pre-processed version.)

python inference.py --config ./config/config.yaml

python train.py --config ./config/config.yaml

The code is partially built based on R2ET.

The dataset is taken from Adobe Mixamo.

The Chamfer Distance is adapted from ChamferDistancePytorch.

The shape encoder and PointNet2_lib is adapted from PCT.

Thanks to all of them.

If you find this work helpful, please consider citing it as follows:

@InProceedings{Yang_2025_STaR,
    author    = {Yang, Xiaohang and Wang, Qing and Yang, Jiahao and Slabaugh, Gregory and Yuan, Shanxin},
    title     = {STaR: Seamless Spatial-Temporal Aware Motion Retargeting with Penetration and Consistency Constraints},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {Oct},
    year      = {2025}
}