Conf-Net: Toward High-Confidence Dense 3D Point-Cloud with Error-Map Prediction

1 code implementation • 23 Jul 2019 • Hamid Hekmatian, Jingfu Jin, Samir Al-Stouhi

Using our predicted error-map, we demonstrate that by up-filling a LiDAR point cloud from 18, 000 points to 285, 000 points, versus 300, 000 points for full depth, we can reduce the RMSE error from 1004 to 399.

Autonomous Driving Depth Completion +1

Towards Full Automated Drive in Urban Environments: A Demonstration in GoMentum Station, California

no code implementations • 2 May 2017 • Akansel Cosgun, Lichao Ma, Jimmy Chiu, Jiawei Huang, Mahmut Demir, Alexandre Miranda Anon, Thang Lian, Hasan Tafish, Samir Al-Stouhi

Each year, millions of motor vehicle traffic accidents all over the world cause a large number of fatalities, injuries and significant material loss.