26 lines
No EOL
1.7 KiB
Markdown
26 lines
No EOL
1.7 KiB
Markdown
## Code to process the HOT3D dataset
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## Usage:
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Step 1: Follow the instructions at the official repository https://github.com/facebookresearch/hot3d to prepare the environment and download the dataset. You should also enable jupyter because the processing codes are run on jupyter.
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Step 2: Set 'dataset_path', 'dataset_processed_path', 'object_library_path', and 'mano_hand_model_path' in 'hot3d_aria_preprocessing.ipynb', put 'hot3d_aria_preprocessing.ipynb', 'hot3d_aria_scene.csv', 'hot3d_objects.csv', and 'utils' into the official repository ('hot3d/hot3d/'), and run it to process the dataset.
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Step 3: It is optional but highly recommended to set 'data_path', 'object_library_path', and 'mano_hand_model_path' in 'hot3d_aria_visualisation.ipynb', put 'hot3d_aria_visualisation.ipynb' and 'mano_hand_pose_init' into the official repository ('hot3d/hot3d/'), and run it to visualise and get familiar with the dataset.
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## Citations
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```bibtex
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@inproceedings{hu25hoigaze,
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title={HOIGaze: Gaze Estimation During Hand-Object Interactions in Extended Reality Exploiting Eye-Hand-Head Coordination},
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author={Hu, Zhiming and Haeufle, Daniel and Schmitt, Syn and Bulling, Andreas},
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booktitle={Proceedings of the 2025 ACM Special Interest Group on Computer Graphics and Interactive Techniques},
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year={2025}}
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@article{banerjee2024introducing,
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title={Introducing HOT3D: An Egocentric Dataset for 3D Hand and Object Tracking},
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author={Banerjee, Prithviraj and Shkodrani, Sindi and Moulon, Pierre and Hampali, Shreyas and Zhang, Fan and Fountain, Jade and Miller, Edward and Basol, Selen and Newcombe, Richard and Wang, Robert and others},
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journal={arXiv preprint arXiv:2406.09598},
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year={2024}}
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``` |