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POINT CLOUD SEGMENTATION METHOD, COMPUTER-READABLE STORAGE MEDIUM AND COMPUTER DEVICE

机译:点云分割方法,计算机可读存储介质和计算机设备

摘要

Disclosed are a point cloud segmentation method, a computer-readable storage medium and a computer device. The method comprises: encoding a point cloud to be processed to obtain a shared feature (S202), the shared feature referring to a feature shared at a semantic level and an instance level; decoding the shared feature according to different decoding modes to respectively obtain a semantic feature and an instance feature (S204); adapting the semantic feature to an instance feature space and then fusing same with the instance feature to obtain a semantic fused instance feature of the point cloud, the semantic fused instance feature representing an instance feature fused with a semantic feature (S206); dividing the semantic fused instance feature of the point cloud to obtain a semantic fused instance feature of each point in the point cloud (S208); and determining, according to the semantic fused instance feature of each point, an instance category to which each point belongs (210). By means of the method, the efficiency of point cloud segmentation is improved.
机译:公开了一种点云分割方法,计算机可读存储介质和计算机设备。该方法包括:编码要处理的点云以获得共享特征(S202),参考在语义级别和实例级别共享的特征的共享特征;根据不同的解码模式解码共享功能,分别获得语义特征和实例特征(S204);将语义功能调整为实例特征空间,然后与实例功能相同,以获取点云的语义融合实例特征,表示与语义功能融合的实例功能的语义融合实例特征(S206);划分点云的语义融合实例特征,以获取点云中每个点的语义融合实例特征(S208);根据每个点的语义融合实例特征,确定每个点所属的实例类别(210)。借助于该方法,提高了点云分段的效率。

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