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--- |
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license: apache-2.0 |
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task_categories: |
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- robotics |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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dataset_info: |
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features: |
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- name: camera_images |
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list: image |
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- name: depth_images |
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list: image |
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- name: normal_images |
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list: image |
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- name: frame_id |
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dtype: int32 |
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- name: scene_id |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 3671744232.849 |
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num_examples: 1473 |
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download_size: 3336228908 |
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dataset_size: 3671744232.849 |
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--- |
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# RoboTransfer-RealData |
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[**Project Page**](https://horizonrobotics.github.io/robot_lab/robotransfer) | [**Paper**](https://huggingface.co/papers/2505.23171) | [**GitHub**](https://github.com/HorizonRobotics/RoboTransfer) |
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RoboTransfer-RealData is a real-world robotic manipulation dataset collected using the ALOHA-AgileX robot system. It was introduced as part of the paper **"RoboTransfer: Controllable Geometry-Consistent Video Diffusion for Manipulation Policy Transfer"**. |
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The dataset contains real-world trajectories used to evaluate policy transfer from synthetic data generated by RoboTransfer, a diffusion-based framework designed for geometry-consistent robotic data synthesis. |
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## Dataset Description |
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The dataset includes multi-modal visual data for robotic tasks: |
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- `camera_images`: RGB frames captured from the robot's camera system. |
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- `depth_images`: Corresponding depth maps for geometric conditioning. |
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- `normal_images`: Estimated surface normal maps. |
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- `frame_id`: The sequential index of the frame. |
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- `scene_id`: Identifier for specific recorded scenes. |
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## Usage |
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As specified in the [RoboTransfer GitHub repository](https://github.com/HorizonRobotics/RoboTransfer), you can process raw RGB images from this dataset into the RoboTransfer format with geometric conditioning using the following script: |
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```bash |
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script/process_real.sh |
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``` |
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## Citation |
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If you use this dataset or the RoboTransfer framework in your research, please cite: |
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```bibtex |
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@misc{liu2025robotransfergeometryconsistentvideodiffusion, |
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title={RoboTransfer: Geometry-Consistent Video Diffusion for Robotic Visual Policy Transfer}, |
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author={Liu Liu and Xiaofeng Wang and Guosheng Zhao and Keyu Li and Wenkang Qin and Jiaxiong Qiu and Zheng Zhu and Guan Huang and Zhizhong Su}, |
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year={2025}, |
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eprint={2505.23171}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2505.23171}, |
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} |
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``` |
