Uncertainty from Motion for DNN Monocular Depth Estimation

Deployment of deep neural networks (DNNs) for monocular depth estimation in safety-critical scenarios on resource-constrained platforms requires well-calibrated and efficient uncertainty estimates. However, many popular uncertainty estimation techniques, including state-of-the-art ensembles and popu...

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Bibliographic Details
Main Authors: Sudhakar, Soumya (Author), Sze, Vivienne (Author), Karaman, Sertac (Author)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: 2022-04-06T15:22:45Z.
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