J-MOD${}^2$: Joint Monocular Obstacle Detection and Depth Estimation

Michele Mancini, Gabriele Costante, Paolo Valigi +1

In this work, we propose an end-to-end deep architecture that jointly learns to detect obstacles and estimate their depth for MAV flight applications. Most of the existing approach…