Problem
-------------
Predict human motion from static image

http://www-personal.umich.edu/~ywchao/pictures/cvpr2017.png

Approach
----------
1. 2d pose sequence generator
2. convert 2d pose to 3d skeleton

https://image.ibb.co/eeBRxv/3D_PFNet.png

https://image.ibb.co/kERaVQ/Forecasting_Human_Dynamics_from_Static_Images_architecture.png


3 Step training strategy
-------------------------
1. Train human 2d pose extractor using annotated video with 2d joint positions
2. 3d skeleton extractor: project mocap data to 2d and use as ground truth for training the 2d->3d skeleton converter
3. Full network training


Datasets
-----------
1.  Penn Action - Annotated human pose in sports image sequences: bench_press, jumping_jacks, pull_ups...
2. MPII - human action videos with annotated single frame
3. Human3.6M - video, depth and mocap. action include: sitting, purchasing, waiting




Evaluation
-------------
On the following tasks:
1. 2D pose forecasting 
2. 3D pose recovery