> Significantly, the input is a sparse dataset.
ie. Few source images vs. traditional photogrammetry.
This uses dozens or hundreds of images, which isn't usually necessary for traditional photogrammetry that maps photos to hard surfaces with textures.
I think what you noted about volumes is the significant part. Complex objects with fine detail and view dependent reflections are the part that shines here over photogrammetry, but it does take a lot of images. I didn't see anything in the paper that dealt with transparency.
This uses dozens or hundreds of images, which isn't usually necessary for traditional photogrammetry that maps photos to hard surfaces with textures.
I think what you noted about volumes is the significant part. Complex objects with fine detail and view dependent reflections are the part that shines here over photogrammetry, but it does take a lot of images. I didn't see anything in the paper that dealt with transparency.