Both VisualSfM and OpenSfM use similar methodology (incremental structure from motion) to reconstruct 3D scene points and camera positions from photos.

And yes, you can build your own tools (even commercially) with OpenSfM.

I am curious how the quality compares and if they have common library dependencies.

Exactly, the convnet is applied on 2d pixels instead of on 3D point clouds. If one have labelled 3D points (e.g. if a point is part of a car or not), one can train a network for recognition directly on 3D points.

Nice. I wonder if this could be used for robot navigation. The segmented point clouds especially are useful.

Been looking forward to a DIY Roomba project using point clouds and neural nets for navigation

Yes. We can apply different heuristics to remove outlier points. One interesting way to do it will be to train a neural network to refine the dense point cloud.