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We present a prior for manifold structured data, such as surfaces of 3D shapes, where deep neural networks are adopted to reconstruct a target shape using gradient descent starting from a random initialization.
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Maxim Tatarchenko, Alexey Dosovitskiy, and Thomas Brox · 2016
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Learning Representations and Generative Models For 3D Point Clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas J Guibas · 2018
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Matheus Gadelha, Rui Wang, and Subhransu Maji · 2018
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Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers
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Unsupervised 3D Shape Induction from 2D Views of Multiple Objects
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Deep image prior
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A Bayesian Perspective on the Deep Image Prior
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Learning shape templates with structured implicit functions
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