Add dataset card for LeHome simulation assets (#1)

- Add dataset card for LeHome simulation assets (cebec886b2272b1077ab9d7172b26b20867bc04c)
- correct citation (2433096127c0d90c7051e51c6d79d42bf758fe3d)
- correct readme (65d6e6817cb47d0bca36ffb43a19818f456769cb)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

README.md

@@ -1,3 +1,42 @@
 ---
 license: cc-by-4.0
----
+task_categories:
+  - robotics
+---
+
+# LeHome: A Simulation Environment for Deformable Object Manipulation in Household Scenarios
+
+LeHome is a high-fidelity simulation platform designed for manipulating deformable objects (such as garments and food items) in household scenarios. It integrates various household environments and supports multiple robotic embodiments, emphasizing low-cost robots for end-to-end evaluation.
+
+- **Paper:** [LeHome: A Simulation Environment for Deformable Object Manipulation in Household Scenarios](https://huggingface.co/papers/2604.22363)
+- **Project Page:** [https://lehome-web.github.io/](https://lehome-web.github.io/)
+- **GitHub Repository:** [https://github.com/lehome-official/lehome](https://github.com/lehome-official/lehome)
+
+## Assets & Data Preparation
+
+This repository contains the required simulation assets (Materials, scenes, objects, and robots). Install or update the Hugging Face CLI, then download the assets:
+
+```bash
+# Install or update the Hugging Face CLI
+pip install --upgrade huggingface_hub
+
+# This creates the Assets/ directory with the required simulation resources
+hf download lehome/lehome_release --repo-type dataset --local-dir Assets
+```
+
+For detailed information on environment setup, dataset collection, and training, please refer to the [official documentation](https://github.com/lehome-official/lehome#documentation-index).
+
+## Citation
+
+```bibtex
+@inproceedings{li2026lehome,
+  title={{LeHome}: A Simulation Environment for Deformable Object Manipulation in Household Scenarios},
+  author={Zeyi Li and Yushi Yang and Shawn Xie and Kyle Xu and Tianxing Chen and Yuran Wang and Zhenhao Shen and Yan Shen and Yue Chen and Wenjun Li and Yukun Zheng and Chaorui Zhang and Siyi Lin and Fei Teng and Hongjun Yang and Ming Chen and Steve Xie and Ruihai Wu},
+  booktitle={2026 IEEE International Conference on Robotics and Automation (ICRA)},
+  year={2026},
+  eprint={2604.22363},
+  archivePrefix={arXiv},
+  primaryClass={cs.RO},
+  url={https://arxiv.org/abs/2604.22363}
+}
+```