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Interpolation-Aware Padding for 3D Sparse Convolutional Neural Networks
[article]
2021
arXiv
pre-print
Sparse voxel-based 3D convolutional neural networks (CNNs) are widely used for various 3D vision tasks. Sparse voxel-based 3D CNNs create sparse non-empty voxels from the 3D input and perform 3D convolution operations on them only. We propose a simple yet effective padding scheme --- interpolation-aware padding to pad a few empty voxels adjacent to the non-empty voxels and involve them in the 3D CNN computation so that all neighboring voxels exist when computing point-wise features via the
arXiv:2108.06925v1
fatcat:5rgz3j2r4nga5o7bquj7qbzz7q