First dataset of dressed humans with specific geometry representation for the clothes. It contains ~2 Million images with 40 male/40 female performing 70 actions. Every subject-action sequence is captured from 4 camera views and annotated with: RGB, 3D skeleton, body part and cloth segmentation masks, depth map, optical flow, and camera parameters.
We can NOT share the 3D meshes nor raw files of the models for copyright reasons. The actions used are from the CMU MoCap database.
- Train: woman01-woman33 man01-man33
- Test: woman34-woman40 man34-man40
Download jupyter notebook. You can use the sample dataset. Full dataset can be download in the dataset website.
conda create -n 3dpeople
source activate 3dpeople
conda install matplotlib opencv pillow scipy
conda install -c conda-forge ipywidgets=7.2.1
conda install -c plotly chart-studio
jupyter nbextension enable --py widgetsnbextension
jupyter notebook vis_dataset.ipynb
Inside notebook select the sequence to visualize: "seq_name=..." in first cell
@inproceedings{pumarola20193dpeople,
title={{3DPeople: Modeling the Geometry of Dressed Humans}},
author={Pumarola, Albert and Sanchez, Jordi and Choi, Gary and Sanfeliu, Alberto and Moreno-Noguer, Francesc},
booktitle={International Conference in Computer Vision (ICCV)},
year={2019}
}