59 citations · 59 across the 2 of their papers we have counts for
2 papers
cs.LG2017★ 59 cited
J-MOD: 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…
cs.RO2016
Fast Robust Monocular Depth Estimation for Obstacle Detection with Fully Convolutional Networks
Michele Mancini, Gabriele Costante, Paolo Valigi +1
Obstacle Detection is a central problem for any robotic system, and critical for autonomous systems that travel at high speeds in unpredictable environment. This is often achieved…