Yes I did come across Gibsonenv and it looks great for indoor scenes.

As far as photogrammetry of forest trails, I found it to be very computationally intensive (taking a GCE 32 core instance 30+ hours using 90+GB of ram to compute a scene, only with errors that made it unusable). It felt very heavy handed and given all the great work I've seen in scene understanding using neural nets, it seems like deep learning would be a promising approach here. Maybe there is commercial photogrammetry software that has better pipelines, but I want to be able to compute my scenes on linux and use hundreds of images.

I did my computation with OpenSFM and OpenMVS. Both wonderful projects for being free and open source. I did get a lot of great results. But I am convinced a simpler way is possible with deep learning.