It looks like the update to https://www.qualcomm.com/news/onq/2022/07/enabling-machines-to-efficiently-perceive-the-world-in-3d , In July they were doing similar depth estimation.

> Depth estimation and 3D reconstruction is the perception task of creating 3D models of scenes and objects from 2D images. Our research leverages input configurations including a single image, stereo images, and 3D point clouds. We’ve developed SOTA supervised and self-supervised learning methods for monocular and stereo images with transformer models that are not only highly efficient but also very accurate. Beyond the model architecture, our full-stack optimization includes using neural architecture search...

That press article and the DONNA page keep it mostly high level / architecture though