Depth Sensing Beyond LiDAR Range

Kai Zhang, Jiaxin Xie, Noah Snavely, Qifeng Chen; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 1692-1700

Abstract


Depth sensing is a critical component of autonomous driving technologies, but today's LiDAR- or stereo camera- based solutions have limited range. We seek to increase the maximum range of self-driving vehicles' depth perception modules for the sake of better safety. To that end, we propose a novel three-camera system that utilizes small field of view cameras. Our system, along with our novel algorithm for computing metric depth, does not require full pre-calibration and can output dense depth maps with practically acceptable accuracy for scenes and objects at long distances not well covered by most commercial LiDARs.

Related Material


[pdf] [arXiv]
[bibtex]
@InProceedings{Zhang_2020_CVPR,
author = {Zhang, Kai and Xie, Jiaxin and Snavely, Noah and Chen, Qifeng},
title = {Depth Sensing Beyond LiDAR Range},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}