Search Results for author:
Found 1 papers, 1 papers with code
Toward Hierarchical Self-Supervised Monocular Absolute Depth Estimation for Autonomous Driving Applications
Our contributions are twofold: a) a novel dense connected prediction (DCP) layer is proposed to provide better object-level depth estimation and b) specifically for autonomous driving scenarios, dense geometrical constrains (DGC) is introduced so that precise scale factor can be recovered without additional cost for autonomous vehicles.
Ranked #54 on
Monocular Depth Estimation
on KITTI Eigen split
Cannot find the paper you are looking for? You can
Submit a new open access paper.
