CPC G06N 3/04 (2013.01) [G06F 16/9027 (2019.01); G06F 17/15 (2013.01); G06N 3/08 (2013.01)] | 20 Claims |
1. A device comprising:
a memory configured to store an octree representing a three-dimensional shape, nodes of the octree including an empty node and a non-empty node, the empty node excluding the three-dimensional shape and being a leaf node of the octree, and the non-empty node including at least a part of the three-dimensional shape; and
a processing unit coupled to the memory and configured to perform acts including:
obtaining the octree representing the three-dimensional shape from the memory, including one or more of: an index of a node of the octree, a label of a node of the octree, shape data of a node of the octree, a hierarchical structure of the octree; and
for a node in the octree with a depth associated with a convolutional layer of a convolutional neural network, performing a convolutional operation of the convolutional layer to obtain an output of the convolutional layer.
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10. A computer-implemented method comprising:
obtaining an octree representing a three-dimensional shape, nodes of the octree including an empty node and a non-empty node, the empty node excluding the three-dimensional shape and being a leaf node of the octree, and the non-empty node including at least a part of the three-dimensional shape;
for a node in the octree with a depth associated with a convolutional layer of a convolutional neural network, performing a convolutional operation of the convolutional layer to obtain an output of the convolutional layer; and
performing a down-sampling operation on shape data of a node of the octree, or an up-sampling operation on shape data of a node of the octree, or both.
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