A depth completion network trained on synthetic field-robotics scenes predicts dense metric depth from extremely sparse real measurements and runs in real time on embedded hardware in unseen outdoor environments.
Sparse-to-dense: Depth pre- diction from sparse depth samples and a single image
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Depth Completion in Unseen Field Robotics Environments Using Extremely Sparse Depth Measurements
A depth completion network trained on synthetic field-robotics scenes predicts dense metric depth from extremely sparse real measurements and runs in real time on embedded hardware in unseen outdoor environments.