Self-supervised sparse-to-dense: Self-supervised depth completion from LiDAR and monocular camera
© 2019 IEEE. Depth completion, the technique of estimating a dense depth image from sparse depth measurements, has a variety of applications in robotics and autonomous driving. However, depth completion faces 3 main challenges: the irregularly spaced pattern in the sparse depth input, the difficulty...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
IEEE,
2020-08-12T17:05:50Z.
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| Subjects: | |
| Online Access: | Get fulltext |