human-motion-prediction

Pytorch implementation of:

Julieta Martinez, Michael J. Black, Javier Romero. On human motion prediction using recurrent neural networks. In CVPR 17.

It can be found on arxiv as well: https://arxiv.org/pdf/1705.02445.pdf

The code in the original repository was written by Julieta Martinez and Javier Romero and is accessible here.

If you have any comment on this fork you can email me at [enriccorona93@gmail.com]

Dependencies

• h5py -- to save samples
• Pytorch

Get this code and the data

First things first, clone this repo and get the human3.6m dataset on exponential map format.

git clone git@github.com:cimat-ris/human-motion-prediction-pytorch.git
cd human-motion-prediction-pytorch
mkdir data
cd data
# Download this file: https://drive.google.com/file/d/1hqE6GrWZTBjVzmbehUBO7NTrbEgDNqbH/view?usp=sharing
wget https://doc-14-bg-docs.googleusercontent.com/docs/securesc/alrk11iv5mn7ii0ag904975ub4luqi8q/kc4[…]827653287620&hash=ekulqrqhse0c8ie2paamn1tjuhkvof3k
unzip h3.6m.zip
rm h3.6m.zip
cd ..

Quick demo and visualization

For a quick demo, you can train for a few iterations and visualize the outputs of your model.

To train the model, run

python src/train.py --action walking --seq_length_out 25 --iterations 10000

To test the model on one sample, run

python src/test.py --action walking --seq_length_out 25 --iterations 10000 --load 10000

Finally, to visualize the samples run

python src/animate.py

This should create a visualization similar to this one

You can substitute the --action walking parameter for any action in

["directions", "discussion", "eating", "greeting", "phoning",
 "posing", "purchases", "sitting", "sittingdown", "smoking",
 "takingphoto", "waiting", "walking", "walkingdog", "walkingtogether"]

or --action all (default) to train on all actions.

Citing

If you use our code, please cite our work

@inproceedings{julieta2017motion,
  title={On human motion prediction using recurrent neural networks},
  author={Martinez, Julieta and Black, Michael J. and Romero, Javier},
  booktitle={CVPR},
  year={2017}
}

Acknowledgments

The pre-processed human 3.6m dataset and some of our evaluation code (specially under src/data_utils.py) was ported/adapted from SRNN by @asheshjain399.

Licence

MIT