Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image

© 2018 IEEE. We consider the problem of dense depth prediction from a sparse set of depth measurements and a single RGB image. Since depth estimation from monocular images alone is inherently ambiguous and unreliable, to attain a higher level of robustness and accuracy, we introduce additional spars...

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Bibliographic Details
Main Authors: Ma, Fangchang (Author), Karaman, Sertac (Author)
Other Authors: Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2021-11-09T18:26:52Z.
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