Depth Sensing Beyond LiDAR Range
Kai Zhang, Jiaxin Xie, Noah Snavely, Qifeng Chen
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.
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Cited by top-tier papers2
- R4D: Utilizing Reference Objects for Long-Range Distance EstimationYingwei Li, Tiffany L. Chen, Maya Kabkab, Ruichi Yu et al.ICLR 2022 · 7 citations
- Augmenting Depth Estimation with Geospatial ContextScott Workman, Hunter BlantonICCV 2021 · 6 citations
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