Is there source code for generating the graphs?

Hi, gods of 3d reconstruction!

I send good wishes and gratitude from your fans at UMD, Maryland, U.S… Big THANK YOU for posting your code! A few questions:

1. Does the repository include the routines for generating the graph data? (I noticed some things for node processing in csrc/cpu/graph_proc.cpp, e.g. sample_nodes, but no actual usages besides imports in model.py and dataset.py. Are those it, or is there something else?)

2. If the answer to (1) is ‘yes’, could you provide a quick example on how these can be used to generate the graphs?

3. If the answer to (1) is ‘no’, can you provide any pointers to existing code that can be used to generate the graphs?

[pablopalafox]

hey @Algomorph! thanks a lot for your interest!

So we definitely have in mind to also release the part for generating the graph data. As you point out, in csrc there are some of the routines we use for generating the data, but indeed the scripts for generating the data are not released. Probably in some weeks after a deadline we have, we’ll release it 😃 I’ll keep you posted

[AljazBozic]

Hi @Algomorph! The code is actually intended to generate training data for NeuralTracking network, so it is assumed that scene flow ground truth is given (from the DeepDeform dataset). But if you want to generate graphs at test time, you would need to adapt it slightly, to generate mesh without scene flow image. Then you also cannot generate ground truth node deformations, but that is actually what you want to compute in any case using the deformation graph, you don’t really have the ground truth at test time. Let me know if there is any confusion about it.