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Dilated Point Convolutions: On the Receptive Field Size of Point Convolutions on 3D Point Clouds
[article]
2020
arXiv
pre-print
In this work, we propose Dilated Point Convolutions (DPC). In a thorough ablation study, we show that the receptive field size is directly related to the performance of 3D point cloud processing tasks, including semantic segmentation and object classification. Point convolutions are widely used to efficiently process 3D data representations such as point clouds or graphs. However, we observe that the receptive field size of recent point convolutional networks is inherently limited. Our dilated
arXiv:1907.12046v3
fatcat:57jqxvwdobfxfnx4htwbcvafs4