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A Point Set Generation Network for 3D Object Reconstruction from a Single Image
[article]
2016
arXiv
pre-print
Generation of 3D data by deep neural network has been attracting increasing attention in the research community. The majority of extant works resort to regular representations such as volumetric grids or collection of images; however, these representations obscure the natural invariance of 3D shapes under geometric transformations and also suffer from a number of other issues. In this paper we address the problem of 3D reconstruction from a single image, generating a straight-forward form of
arXiv:1612.00603v2
fatcat:5cqdthedjrblnfwbmdqhf23wym