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GraphX-Convolution for Point Cloud Deformation in 2D-to-3D Conversion
[article]
2019
arXiv
pre-print
In this paper, we present a novel deep method to reconstruct a point cloud of an object from a single still image. Prior arts in the field struggle to reconstruct an accurate and scalable 3D model due to either the inefficient and expensive 3D representations, the dependency between the output and number of model parameters or the lack of a suitable computing operation. We propose to overcome these by deforming a random point cloud to the object shape through two steps: feature blending and
arXiv:1911.06600v1
fatcat:abjucudg2zeopjproq72vsvtra