autonomousvision / occupancy_networks

This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"
https://avg.is.tuebingen.mpg.de/publications/occupancy-networks
MIT License
1.48k stars 291 forks source link

The chamfer-L1 loss for PSGN #103

Open yigepingzi opened 2 years ago

yigepingzi commented 2 years ago

Inside the Supplementary Material, the definition of Chamfer -L1 has a term: the surface area of the mesh. But in the evaluation code, the surface area is implemented as the summation of the points number. Atals/Pix2mesh/Onet use 100k sampled points from predicted mesh and 100k sampled gt points to calculate the Chamfer-L1 loss. But how about PSGN? PSGN only predict 1024 points, is the metric reported in the paper are calculated on 1024 points instead of 100k points? Is this a fair comparison?

Really confused. Hope someone can give me some insight? Thank you very much.