| --- |
| license: mit |
| pretty_name: Humans with Collisions (HwC) Pose & Motion Dataset |
| task_categories: |
| - robotics |
| - other |
| tags: |
| - 3d-graphics |
| - smpl-h |
| - collision-resolution |
| - human-pose |
| - motion-analysis |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/dataset/train_list.csv |
| - split: test |
| path: data/dataset/test_list.csv |
| --- |
| |
| # 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](https://arxiv.org/abs/2606.29686) |
| - **Code Repository:** [PoseShield on GitHub](https://github.com/Tencent-Hunyuan/HY-Motion-1.0) (or project repo) |
|
|
| --- |
|
|
| ## 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`). |
|
|
| --- |
|
|
| ## 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: |
|
|
| ```bash |
| 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: |
|
|
| ```python |
| 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: |
|
|
| ```bibtex |
| @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} |
| } |
| ``` |
|
|
