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.
Learning depth from single monocular images using deep convolu- tional neural fields
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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.