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+# PHUMA: Physically-Grounded Humanoid Locomotion Dataset
+
+This repository provides physically-grounded humanoid locomotion dataset, PHUMA.
+
+PHUMA leverages large-scale human motion data while overcoming physical artifacts through careful data curation and physics-constrained retargeting to create a high-quality humanoid locomotion dataset.
+
+For detailed results, implementation notes, and videos, please visit our [paper](https://arxiv.org/abs/2510.26236), [project page](https://davian-robotics.github.io/PHUMA/) and [GitHub repository](https://github.com/DAVIAN-Robotics/PHUMA).
+
+## Dataset Structure
+
+The dataset contains retargeted data for 2 different humanoids:
+
+```
+data/
+├── g1/          # Humanoid configuration g1
+└── h1_2/        # Humanoid configuration h1_2
+```
+
+## Data Format
+
+Each `.npy` file in the dataset follows a consistent structure:
+
+```python
+{
+    'root_trans': (num_frames, 3),      # Root translation (x, y, z)
+    'root_ori': (num_frames, 4),        # Root orientation quaternion (x, y, z, w)
+    'dof_pos': (num_frames, num_dof),   # Degrees of freedom positions for all joints
+    'fps': fps                          # Frame rate (frames per second)
+}
+```
+
+### Field Descriptions
+
+- **root_trans**: Root joint translation in 3D space `(x, y, z)` for each frame
+- **root_ori**: Root joint orientation as quaternion `(x, y, z, w)` for each frame
+- **dof_pos**: Joint positions for all degrees of freedom across frames
+- **fps**: Frame rate of the motion sequence
+
+## Citation
+
+If you find this dataset useful in your research, please cite our paper:
+
+```bibtex
+@article{lee2025phuma,
+    title={PHUMA: Physically-Grounded Humanoid Locomotion Dataset}, 
+    author={Kyungmin Lee and Sibeen Kim and Minho Park and Hyunseung Kim and Dongyoon Hwang and Hojoon Lee and Jaegul Choo},
+    journal={arXiv preprint arXiv:2510.26236},
+    year={2025}
+}
+```