Visualization-of-Human3.6M-Dataset
Plot and save the ground truth and predicted results of human 3.6 M and CMU mocap dataset.
human-motion-prediction
This is the code for visulalizing the ground truth and predicted results of human 3.6M dataset.
To save the gif for ground truth data, ru
python forward_kinematics.py --save --save_name "figs/walking.gif"
To save visualization for trained modeld sample.h5, run
python forward_kinematics.py --sample_name samples.h5 --save --save_name "figs/walking_py_0.gif"
Finally, to visualize the samples run
python forward_kinematics.py
This should create a visualization similar to this one
In data folder it has only subject 5 due to space constraint.
To download full dataset follow this
wget http://www.cs.stanford.edu/people/ashesh/h3.6m.zip
Acknowledgments
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 this repository was written by Julieta Martinez and Javier Romero.
Thank you
Gaurav
