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- # Retargeted AMASS for Robotics
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-
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- ## Project Overview
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-
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- This project aims to retarget motion data from the AMASS dataset to various robot models and open-source the retargeted data to facilitate research and applications in robotics and human-robot interaction. AMASS (Archive of Motion Capture as Surface Shapes) is a high-quality human motion capture dataset, and the SMPL-X model is a powerful tool for generating realistic human motion data.
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-
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- By adapting the motion data from AMASS to different robot models, we hope to provide a more diverse and accessible motion dataset for robot training and human-robot interaction.
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-
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- ## Dataset Content
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-
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- This open-source project includes the following:
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- 1. **Retargeted Motions**: Motion files retargeted from AMASS to various robot models.
13
-
14
- - **Unitree G1**:
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-
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- <iframe src="//player.bilibili.com/player.html?bvid=BV1zd6iYkEZ2&page=1&high_quality=1&danmaku=0" allowfullscreen="allowfullscreen" width="100%" height="500" scrolling="no" frameborder="0" sandbox="allow-top-navigation allow-same-origin allow-forms allow-scripts"></iframe>
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-
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- The retargeted motions for the Unitree G1 robot are generated based on the official open-source model provided by Unitree.
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-
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- https://github.com/unitreerobotics/unitree_ros/blob/master/robots/g1_description/g1_29dof_lock_waist_rev_1_0.xml
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-
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- The joint positions comply with the constraints defined in the XML file.
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-
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- data shape:[-1,36]
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-
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- ​ 0:3 root world position
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-
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- ​ 3:7 root quaternion rotation, order: xyzw
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-
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- ​ 7:36 joint positions
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-
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- joint order:
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-
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- ```txt
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- left_hip_pitch_joint
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- left_hip_roll_joint
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- left_hip_yaw_joint
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- left_knee_joint
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- left_ankle_pitch_joint
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- left_ankle_roll_joint
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- right_hip_pitch_joint
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- right_hip_roll_joint
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- right_hip_yaw_joint
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- right_knee_joint
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- right_ankle_pitch_joint
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- right_ankle_roll_joint
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- waist_yaw_joint
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- waist_roll_joint
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- waist_pitch_joint
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- left_shoulder_pitch_joint
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- left_shoulder_roll_joint
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- left_shoulder_yaw_joint
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- left_elbow_joint
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- left_wrist_roll_joint
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- left_wrist_pitch_joint
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- left_wrist_yaw_joint
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- right_shoulder_pitch_joint
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- right_shoulder_roll_joint
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- right_shoulder_yaw_joint
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- right_elbow_joint
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- right_wrist_roll_joint
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- right_wrist_pitch_joint
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- right_wrist_yaw_joint
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- ```
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-
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- - **Others**: Future Updates
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-
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-
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-
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- 2. **Usage Examples**: Code examples on how to use the retargeted data.
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-
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- ./g1/visualize.py
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-
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-
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-
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- 3. **License Files**: Original license information for each sub-dataset within AMASS.
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-
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-
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-
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- ## License
81
-
82
- The retargeted data in this project is derived from the AMASS dataset and therefore adheres to the original license terms of AMASS. Each sub-dataset within AMASS may have different licenses, so please ensure compliance with the following requirements when using the data:
83
- - **Propagate Original Licenses**: When using or distributing the retargeted data, you must include and comply with the original licenses of the sub-datasets within AMASS.
84
- - **Attribution Requirements**: Properly cite this work and the original authors and sources of the AMASS dataset and its sub-datasets.
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-
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- For detailed license information, please refer to the `LICENSE` file in this project.
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-
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-
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-
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- ## Acknowledgments
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-
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- This project is built on the AMASS dataset and the SMPL-X model. Special thanks to the research team at the Max Planck Institute for Intelligent Systems for providing this valuable resource.
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-
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-
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-
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- ## Citation
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-
98
- If you use the data or code from this project, please cite this work and relevant papers for AMASS and SMPL-X:
99
- ```bibtex
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- @misc{Retargeted_AMASS_R,
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- title={Retargeted AMASS for Robotics},
102
- author={Kun Zhao},
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- url={https://huggingface.co/datasets/fleaven/Retargeted_AMASS_for_robotics}
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- }
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-
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- @inproceedings{AMASS2019,
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- title={AMASS: Archive of Motion Capture as Surface Shapes},
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- author={Mahmood, Naureen and Ghorbani, Nima and Troje, Nikolaus F. and Pons-Moll, Gerard and Black, Michael J.},
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- booktitle={International Conference on Computer Vision (ICCV)},
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- year={2019}
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- }
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-
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- @inproceedings{SMPL-X2019,
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- title={Expressive Body Capture: 3D Hands, Face, and Body from a Single Image},
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- author={Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.},
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- booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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- year={2019}
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- }
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- ```
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-
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- ## Contact
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-
123
- For any questions or suggestions, please contact:
124
- - **Kun Zhao**: [email protected]
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-
126
-
127
-
128
- For more information, follow my Xiaohongshu and Bilibili:
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-
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- https://www.xiaohongshu.com/user/profile/60cdc5360000000001007e33
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-
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  https://space.bilibili.com/678369952
 
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+ ---
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+ license: cc-by-4.0
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+ task_categories:
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+ - robotics
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+ language:
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+ - en
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+ tags:
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+ - AMASS
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+ - Retarget
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+ - Robotics
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+ - Humanoid
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+ pretty_name: Retargeted AMASS for Robotics
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+ size_categories:
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+ - 10K<n<100K
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+ ---
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+ # Retargeted AMASS for Robotics
17
+
18
+ ## Project Overview
19
+
20
+ This project aims to retarget motion data from the AMASS dataset to various robot models and open-source the retargeted data to facilitate research and applications in robotics and human-robot interaction. AMASS (Archive of Motion Capture as Surface Shapes) is a high-quality human motion capture dataset, and the SMPL-X model is a powerful tool for generating realistic human motion data.
21
+
22
+ By adapting the motion data from AMASS to different robot models, we hope to provide a more diverse and accessible motion dataset for robot training and human-robot interaction.
23
+
24
+ ## Dataset Content
25
+
26
+ This open-source project includes the following:
27
+ 1. **Retargeted Motions**: Motion files retargeted from AMASS to various robot models.
28
+
29
+ - **Unitree G1**:
30
+
31
+ <iframe src="//player.bilibili.com/player.html?bvid=BV1zd6iYkEZ2&page=1&high_quality=1&danmaku=0" allowfullscreen="allowfullscreen" width="100%" height="500" scrolling="no" frameborder="0" sandbox="allow-top-navigation allow-same-origin allow-forms allow-scripts"></iframe>
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+
33
+ The retargeted motions for the Unitree G1 robot are generated based on the official open-source model provided by Unitree.
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+
35
+ https://github.com/unitreerobotics/unitree_ros/blob/master/robots/g1_description/g1_29dof_lock_waist_rev_1_0.xml
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+
37
+ The joint positions comply with the constraints defined in the XML file.
38
+
39
+ data shape:[-1,36]
40
+
41
+ ​ 0:3 root world position
42
+
43
+ ​ 3:7 root quaternion rotation, order: xyzw
44
+
45
+ ​ 7:36 joint positions
46
+
47
+ joint order:
48
+
49
+ ```txt
50
+ left_hip_pitch_joint
51
+ left_hip_roll_joint
52
+ left_hip_yaw_joint
53
+ left_knee_joint
54
+ left_ankle_pitch_joint
55
+ left_ankle_roll_joint
56
+ right_hip_pitch_joint
57
+ right_hip_roll_joint
58
+ right_hip_yaw_joint
59
+ right_knee_joint
60
+ right_ankle_pitch_joint
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+ right_ankle_roll_joint
62
+ waist_yaw_joint
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+ waist_roll_joint
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+ waist_pitch_joint
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+ left_shoulder_pitch_joint
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+ left_shoulder_roll_joint
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+ left_shoulder_yaw_joint
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+ left_elbow_joint
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+ left_wrist_roll_joint
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+ left_wrist_pitch_joint
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+ left_wrist_yaw_joint
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+ right_shoulder_pitch_joint
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+ right_shoulder_roll_joint
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+ right_shoulder_yaw_joint
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+ right_elbow_joint
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+ right_wrist_roll_joint
77
+ right_wrist_pitch_joint
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+ right_wrist_yaw_joint
79
+ ```
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+
81
+ - **Others**: Future Updates
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+
83
+
84
+
85
+ 2. **Usage Examples**: Code examples on how to use the retargeted data.
86
+
87
+ ./g1/visualize.py
88
+
89
+
90
+
91
+ 3. **License Files**: Original license information for each sub-dataset within AMASS.
92
+
93
+
94
+
95
+ ## License
96
+
97
+ The retargeted data in this project is derived from the AMASS dataset and therefore adheres to the original license terms of AMASS. Each sub-dataset within AMASS may have different licenses, so please ensure compliance with the following requirements when using the data:
98
+ - **Propagate Original Licenses**: When using or distributing the retargeted data, you must include and comply with the original licenses of the sub-datasets within AMASS.
99
+ - **Attribution Requirements**: Properly cite this work and the original authors and sources of the AMASS dataset and its sub-datasets.
100
+
101
+ For detailed license information, please refer to the `LICENSE` file in this project.
102
+
103
+
104
+
105
+ ## Acknowledgments
106
+
107
+ This project is built on the AMASS dataset and the SMPL-X model. Special thanks to the research team at the Max Planck Institute for Intelligent Systems for providing this valuable resource.
108
+
109
+
110
+
111
+ ## Citation
112
+
113
+ If you use the data or code from this project, please cite this work and relevant papers for AMASS and SMPL-X:
114
+ ```bibtex
115
+ @misc{Retargeted_AMASS_R,
116
+ title={Retargeted AMASS for Robotics},
117
+ author={Kun Zhao},
118
+ url={https://huggingface.co/datasets/fleaven/Retargeted_AMASS_for_robotics}
119
+ }
120
+
121
+ @inproceedings{AMASS2019,
122
+ title={AMASS: Archive of Motion Capture as Surface Shapes},
123
+ author={Mahmood, Naureen and Ghorbani, Nima and Troje, Nikolaus F. and Pons-Moll, Gerard and Black, Michael J.},
124
+ booktitle={International Conference on Computer Vision (ICCV)},
125
+ year={2019}
126
+ }
127
+
128
+ @inproceedings{SMPL-X2019,
129
+ title={Expressive Body Capture: 3D Hands, Face, and Body from a Single Image},
130
+ author={Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.},
131
+ booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
132
+ year={2019}
133
+ }
134
+ ```
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+
136
+ ## Contact
137
+
138
+ For any questions or suggestions, please contact:
139
+ - **Kun Zhao**: [email protected]
140
+
141
+
142
+
143
+ For more information, follow my Xiaohongshu and Bilibili:
144
+
145
+ https://www.xiaohongshu.com/user/profile/60cdc5360000000001007e33
146
+
147
  https://space.bilibili.com/678369952