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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}
}
```
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