If I understand things correctly, this relies extremely heavily on learned prior shapes, meaning it'll guess depth from a monocular image and then go from there

If I understand things correctly, this relies extremely heavily on learned prior shapes, meaning it'll guess depth from a monocular image and then go from there. In line with that, it uses a Vision Transformer like MiDaS (Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer). That's why it can still reconstruct a scene even if the images do not overlap at all: https://twitter.com/JeromeRevaud/status/1763495315389165963 https://twitter.com/JeromeRevaud/status/1763495315389165963 But what that also means is that this is closer to generative AI than to objective measurements. If the image to depth estimation goes very wrong, it might hallucinate shapes that aren't there.