Transcription of PointNet++: Deep Hierarchical Feature Learning on Point ...
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pointnet ++: deep Hierarchical Feature Learning onPoint Sets in a Metric SpaceCharles R. QiLi YiHao SuLeonidas J. GuibasStanford UniversityAbstractFew prior works study deep Learning on Point sets. pointnet [20] is a pioneer in thisdirection. However, by design pointnet does not capture local structures induced bythe metric space points live in, limiting its ability to recognize fine-grained patternsand generalizability to complex scenes. In this work, we introduce a hierarchicalneural network that applies pointnet recursively on a nested partitioning of theinput Point set. By exploiting metric space distances, our network is able to learnlocal features with increasing contextual scales.
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space Charles R. Qi Li Yi Hao Su Leonidas J. Guibas Stanford University Abstract Few prior works study deep learning on point sets. PointNet [20] is a pioneer in this direction. However, by design PointNet does not capture local structures induced by
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