Reproduce the paper results

Launch all the trainings with scripts/launch.py --mode training (remove the trained models in /log if you downloaded them for the demo) OR call ./log/download_pretrained_models.sh.
Launch all the inferences in `scripts/launch.py --mode inference

This populates a global Pandas dataframe with the results called results.csv.

Make the tables : python scripts/make_papertables_from_results.py and check them in the html/ folder.
Make the curves : Run the notebook : The values are hard-coded from the results of my own experiments.
Make the figures : check the generated mesh in the figures/ folder

Difference with the paper

The Meta network predict a Fully Connected Layer (Matrix input_size,ouput_size and Bias) instead of a Adaptive Normalization (Vector input_size and Bias)
The Generalized ablation study suggests that on could get rid of the chamfer loss enterily for slightly better performances.