There is depth information, just not in the form of a mesh. The model learns to compute a function that takes an XYZ position within a volume as input, and ret

There is depth information, just not in the form of a mesh. The model learns to compute a function that takes an XYZ position within a volume as input, and returns color and opacity. You can then render images by tracing rays through this volume. You can pretty easily compute the distance to the first sufficiently-opaque region, or the "average" depth (weighted by each sample's contribution to the final pixel color), at the same time. Another recent Google project figured out a way to approximate these radiance fields with layered, partially transparent images for efficient rendering: https://augmentedperception.github.io/deepviewvideo/ https://augmentedperception.github.io/deepviewvideo/