README.md

June 19, 2023 · View on GitHub

This software was developed by Manuel Kaufmann, Velko Vechev and Dario Mylonopoulos. The original aitviewer codebase is here. I just add a sloper4d_viwer.py file to visualize the SLOPER4D dataset.

Installation

Please install this fork locally

git clone https://github.com/climbingdaily/aitviewer.git
cd aitviewer
pip install -e .

Dependencies

Download the SMPL models to ./data/smpl_models/smpl/

For more advanced installation and for installing SMPL body models, please refer to the documentation .

Run

python sloper4d_viewer.py --pkl_file /path/to/the/pkl

optional parameters

--is_global  True    # whether to show the global translation of the person
--pose  'pose'       # the pose param to visualize, 'pose' or 'opt_pose'
--scene_path  /path/to/the/scenemesh

Projects using the aitviewer

A sampling of projects using the aitviewer. Let us know if you want to be added to this list!

Sun et al., TRACE: 5D Temporal Regression of Avatars with Dynamic Cameras in 3D Environments, CVPR 2023
Fan et al., ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation, CVPR 2023
Dong et al., Shape-aware Multi-Person Pose Estimation from Multi-view Images, ICCV 2021
Kaufmann et al., EM-POSE: 3D Human Pose Estimation from Sparse Electromagnetic Trackers, ICCV 2021
Vechev et al., Computational Design of Kinesthetic Garments, Eurographics 2021
Guo et al., Human Performance Capture from Monocular Video in the Wild, 3DV 2021
Dong and Guo et al., PINA: Learning a Personalized Implicit Neural Avatar from a Single RGB-D Video Sequence, CVPR 2022

Citation

If you use this software, please cite it as below.

@software{Kaufmann_Vechev_aitviewer_2022,
  author = {Kaufmann, Manuel and Vechev, Velko and Mylonopoulos, Dario},
  doi = {10.5281/zenodo.1234},
  month = {7},
  title = {{aitviewer}},
  url = {https://github.com/eth-ait/aitviewer},
  year = {2022}
}