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README.md

@@ -1,3 +1,88 @@
 ---
-license: apache-2.0
+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}
+}
+```