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...
Main Authors: | Ma, Fangchang (Author), Karaman, Sertac (Author) |
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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.
|
Subjects: | |
Online Access: | Get fulltext |
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