ZYYY99/Humans_with_Collision

Humans with Collisions (HwC) Pose & Motion Dataset

This dataset contains the training, evaluation, and benchmark data for the paper:
"PoseShield: Neural Collision Fields for Human Self-Collision Resolution (ECCV 2026)"

• Paper (arXiv): arXiv:2606.29686
• Code Repository: PoseShield on GitHub (or project repo)

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Dataset Structure

The repository contains two main groups of data structured under the data/ directory:

1. HwC Pose Dataset (Single Poses)

Used for training the neural self-collision field and evaluating pose-level collision resolution.

• data/dataset/train_list.csv - List of training sample IDs.
• data/dataset/test_list.csv - List of testing sample IDs.
• data/dataset/augmented_data/ - Folder containing self-colliding SMPL-H body poses (.npz) used as negative training inputs.
• data/dataset/gt_data/ - Folder containing corresponding collision-free ground truth poses (.npz).
• data/dataset_test/ - The HwC 500-pose benchmark subset used for single-pose collision resolution validation, containing body models (.pkl), mesh files (.obj), and visualization references (.png).

2. Motion Dataset (Motion Sequences)

Used for two-stage latent motion optimization and visual/numerical self-collision resolution benchmark.

• data/motion_canonical/ - Folder containing the 100 canonical MotionFix self-intersecting human motion sequences (.npy).

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Usage Instructions

To use this dataset in your project, you can clone this repository directly or download the snapshot programmatically.

Cloning via Git LFS

Make sure you have Git LFS installed to fetch the .npz and .npy files correctly:

git lfs install
git clone https://huggingface.co/datasets/ZYYY99/Humans_with_Collision

Programmatic Download (Python)

You can download the entire folder structure programmatically using the huggingface_hub Python package:

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="ZYYY99/Humans_with_Collision", 
    repo_type="dataset", 
    local_dir="data"
)

Citation

If you use this dataset or the matching method in your research, please cite:

@article{li2026poseshield,
  title={PoseShield: Neural Collision Fields for Human Self-Collision Resolution},
  author={Li, Zhengyuan and Deng, Zeyun and Shen, Yifan and Gui, Liangyan and Xie, Miaolan and Campbell, Joseph and Gao, Xifeng and Wu, Kui and Pan, Zherong and Bera, Aniket},
  journal={arXiv preprint arXiv:2606.29686},
  year={2026}
}