Transcription of IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE …
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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE …
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE1 Deep Learning for 3D Point Clouds: A SurveyYulan Guo , Hanyun Wang , Qingyong Hu , Hao Liu , Li Liu, and Mohammed BennamounAbstract Point cloud learning has lately attracted increasing attention due to its wide applications in many areas, such as computervision, autonomous driving, and robotics. As a dominating technique in AI, deep learning has been successfully used to solve various2D vision problems. However, deep learning on point clouds is still in its infancy due to the unique challenges faced by the processingof point clouds with deep neural networks. Recently, deep learning on point clouds has become even thriving, with numerous methodsbeing proposed to address different problems in this area.
Apple depth cameras) [1]. 3D data acquired by these sensors can provide rich geometric, shape and scale information [2], [3]. Complemented with 2D images, 3D data provides an opportunity for a better understanding of the surrounding environment for machines. 3D data has numerous appli-cations in different areas, including autonomous driving,
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