Abstract: In increasingly complex machine learning tasks, multiple convolutional kernels are essential for extracting diverse features from data. The parallel computation of these kernels becomes ...
Abstract: In this paper, we introduce a novel 3D mesh convolution-based autoencoder for geometry compression, able to deal with irregular mesh data without requiring neither preprocessing nor manifold ...
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