BEHAVE

Repo for BEHAVE: Dataset and Method for Tracking Human Object Interactions, CVPR'22

Link to paper: https://arxiv.org/pdf/2204.06950.pdf

Prerequisites

• I've added my environment files to requirements.txt. You can directly install these packages. Some of them are not necessary but good to have for debugging, visualizations etc. Core packages are listed below.
• Cuda 10.2
• Python 3.7
• Pytorch 1.7.1
• pytorch3d 0.2.0
• Trimesh
• SMPL pytorch from https://github.com/gulvarol/smplpytorch. I have included these files (with required modifications) in this repo.
• Download SMPL from https://smpl.is.tue.mpg.de/

Prepare data

• Download BEHAVE dataset from: https://github.com/xiexh20/behave-dataset
• Use the script utils/voxelize_ho.py to voxelize the human and object point cloud from BEHAVE dataset. This is the input to the network.
• Use the scipt utils/compute_df_ho.py to sample query points and compute distance and correspondence fields. This is the supervision to the network.
• Prepare diffused SMPL from LoopReg, NeurIPS'20, with the script utils/spread_SMPL_function.py
• Make data split for training and testing using the script utils/make_data_split.py
• Download assets: https://nextcloud.mpi-klsb.mpg.de/index.php/s/k4cK24c7SRWEBXo

Download pre-trained models

Coming soon.

Test BEHAVE model

python train.py -mode val -exp_id 01 -ext 01 -suffix 01 -save_name val -split_file assets/data_split_01.pkl -batch_size 12

Train BEHAVE model

python train.py -exp_id 01 -ext 01 -suffix 01 -split_file assets/data_split_01.pkl -batch_size 32 -epochs 150

Cite us:

If you use this code please cite:

@inproceedings{bhatnagar22behave,
    title = {BEHAVE: Dataset and Method for Tracking Human Object Interactions},
    author = {Bhatnagar, Bharat Lal and  Xie, Xianghui and Petrov, Ilya and Sminchisescu, Cristian and Theobalt, Christian and Pons-Moll, Gerard},
    booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {June},
    year = {2022},
}

LICENCE

Copyright (c) 2020 Bharat Lal Bhatnagar, Max-Planck-Gesellschaft

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