Ground segmentation of point clouds remains challenging because of the sparseand unordered data structure . This paper proposes the GSECnet – GroundSegmentation network for Edge Computing . It is designed to be deployable on a low-poweredge computing unit . Remarkably, our framework achieves the inference runtime of 135.2Hz on a desktop platform. Moreover, experiments verify that it is deployedable ona low-power edge computing unit powered 10 watts only . Our proposed framework is evaluated on SemanticKITTI againstboth point-based and discretization-based state-of-the-art learning approaches,and achieves an excellent balance between high accuracy and low computingcomplexity. Remark

Author(s) : Dong He, Jie Cheng, Jong-Hwan Kim

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Keywords : computing - edge - point - gsecnet - unit -

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