Enabling Monocular Depth Perception at the Very Edge

CVPR 2020

Authors: Valentino Peluso, Antonio Cipolletta, Andrea Calimera, Matteo Poggi, Fabio Tosi, Filippo Aleotti, Stefano Mattoccia Description: Depth estimation is crucial in several computer vision applications, and a recent trend aims at inferring such a cue from a single camera through computationally demanding CNNs — precluding their practical deployment in several application contexts characterized by low-power constraints. Purposely, we develop a tiny network tailored to microcontrollers, processing low-resolution images to obtain a coarse depth map of the observed scene. Our solution enables depth perception with minimal power requirements (a few hundreds of mW), accurately enough to pave the way to several high-level applications at-the-edge.