ML Anthology

Depth Sensing Beyond LiDAR Range

Kai Zhang, Jiaxin Xie, Noah Snavely, Qifeng Chen
CVPR 2020
doi:10.1109/CVPR42600.2020.00176 /cvpr/2020/zhang2020cvpr-depth/

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.

PDF CVPR Semantic Scholar

Cite

Text

Zhang et al. "Depth Sensing Beyond LiDAR Range." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020. doi:10.1109/CVPR42600.2020.00176

Markdown

[Zhang et al. "Depth Sensing Beyond LiDAR Range." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020.](https://mlanthology.org/cvpr/2020/zhang2020cvpr-depth/) doi:10.1109/CVPR42600.2020.00176

BibTeX

@inproceedings{zhang2020cvpr-depth,
  title     = {{Depth Sensing Beyond LiDAR Range}},
  author    = {Zhang, Kai and Xie, Jiaxin and Snavely, Noah and Chen, Qifeng},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2020},
  doi       = {10.1109/CVPR42600.2020.00176},
  url       = {https://mlanthology.org/cvpr/2020/zhang2020cvpr-depth/}
}