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In this paper, we present an alternative architecture to the state-of-the-art
in 6D pose - DenseFusion. We changed the architecture of the method in
the depth feature extraction phase. Instead of using the PointNet, as used
in the original DenseFusion, we used global descriptors from the Point
Cloud Library (PCL) to extract features. We made a comparison in terms
of average accuracy between the Ensemble of Shape Functions (ESF),
Viewpoint Feature Histogram (VHF) and the original PointNet.