PCSCNet: Fast 3D semantic segmentation of LiDAR point cloud for autonomous car using point convolution and sparse convolution network

Jaehyun Park; Chansoo Kim; Soyeong Kim; Kichun Jo

doi:10.1016/j.eswa.2022.118815

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PCSCNet: Fast 3D semantic segmentation of LiDAR point cloud for autonomous car using point convolution and sparse convolution network

Jaehyun Park Chansoo Kim Soyeong Kim Kichun Jo

Year: 2022 Journal: Expert Systems with Applications Vol: 212 Pages: 118815-118815 Publisher: Elsevier BV

DOI: 10.1016/j.eswa.2022.118815

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Keywords:

Convolution (computer science) Point cloud Computer science Lidar Segmentation Artificial intelligence Point (geometry) Computer vision Pattern recognition (psychology) Remote sensing Mathematics Geology Geometry Artificial neural network

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Topics

3D Shape Modeling and Analysis

Physical Sciences → Engineering → Computational Mechanics

Remote Sensing and LiDAR Applications

Physical Sciences → Environmental Science → Environmental Engineering

Robotics and Sensor-Based Localization

Physical Sciences → Engineering → Aerospace Engineering

PCSCNet: Fast 3D semantic segmentation of LiDAR point cloud for autonomous car using point convolution and sparse convolution network

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