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- W2890967837 abstract "Depth map estimation techniques from cameras often struggle to accurately estimate the depth of large textureless regions. In this work we present a vision-only method that accurately extracts planar priors from a viewed scene without making any assumptions of the underlying scene layout. Through a fast global labelling, these planar priors can be associated to the individual pixels leading to more complete depth-maps specifically over large, plain and planar regions that tend to dominate the urban environment. When these depth-maps are deployed to the creation of a vision only dense reconstruction over large scales, we demonstrate reconstructions that yield significantly better results in terms of coverage while still maintaining high accuracy." @default.
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- W2890967837 date "2018-05-01" @default.
- W2890967837 modified "2023-09-23" @default.
- W2890967837 title "Fast Global Labelling for Depth-Map Improvement Via Architectural Priors" @default.
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- W2890967837 doi "https://doi.org/10.1109/icra.2018.8460192" @default.
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