Duplicate from USC-GVL/Humanoid-X

Co-authored-by: Siheng Zhao <OliverZhao@users.noreply.huggingface.co>

.gitattributes

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README.md

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+---
+task_categories:
+- robotics
+---
+
+<div align="center">
+<h1> <img src="assets/icon.png" width="50" /> Humanoid-X </h1>
+</div>
+<h5 align="center">
+    <a href="https://usc-gvl.github.io/UH-1/">🌐 Homepage</a> | <a href="https://huggingface.co/datasets/USC-GVL/Humanoid-X">⛁ Dataset</a> | <a href="https://huggingface.co/USC-GVL/UH-1">🤗 Models</a> | <a href="https://arxiv.org/abs/2412.14172">📑 Paper</a> | <a href="https://github.com/sihengz02/UH-1">💻 Code</a>
+</h5>
+
+
+This repo contains the officail dataset for the paper "[Learning from Massive Human Videos for Universal Humanoid Pose Control](https://arxiv.org/abs/2412.14172)"
+If you like our project, please give us a star ⭐ on GitHub for latest update.
+
+![Alt text](assets/teaser.png)
+
+- In this repo, we fully release the text desciption data `texts.zip`, humanoid keypoints data `humanoid_keypoint.zip`, and humanoid actions data `humanoid_action.zip`.
+
+- We only release part of the human poses data (charades subset, kinetics700 subset, and youtube subset) `human_pose.zip` due to license issues. Instead, we provide instructions on how to obtain other parts of human poses data: [HumanML3D/AMASS](https://github.com/EricGuo5513/HumanML3D), [Motion-X](https://github.com/IDEA-Research/Motion-X?tab=readme-ov-file#-dataset-download).
+
+- We release the train, test, and valid set split as `train.txt`, `test.txt`, and `val.txt`.
+
+- We will not release the original Internet videos to protect copyright.
+
+# Dataset Statistics
+
+![Alt text](assets/dataset.png)
+
+# Dataset Collection Pipeline
+
+![Alt text](assets/annotation.png)
+
+# Citation
+
+If you find our work helpful, please cite us:
+
+```bibtex
+@article{mao2024learning,
+  title={Learning from Massive Human Videos for Universal Humanoid Pose Control},
+  author={Mao, Jiageng and Zhao, Siheng and Song, Siqi and Shi, Tianheng and Ye, Junjie and Zhang, Mingtong and Geng, Haoran and Malik, Jitendra and Guizilini, Vitor and Wang, Yue},
+  journal={arXiv preprint arXiv:2412.14172},
+  year={2024}
+}
+```

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