Enhanced Local and Global Learning for Rotation-Invariant Point Cloud Representation
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DOI: 10.1109/mmul.2022.3151906
Abstract: Various studies have been undertaken to learn point cloud representations that are both discriminative and robust. However, most of them suffer from rotation disturbance and insufficient labeled data. To solve the problem of rotation disturbance,… read more here.
Keywords: point cloud; rotation invariant; rotation; enhanced local ... See more keywords
LSLPCT: An Enhanced Local Semantic Learning Transformer for 3-D Point Cloud Analysis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3202823
Abstract: The 3-D point cloud is a common 3-D data representation that has received increasing attention for remote sensing applications. However, processing 3-D point cloud semantics, especially local semantic information, has always been a challenge and… read more here.
Keywords: point cloud; enhanced local; semantic learning; local semantic ... See more keywords