Building 3D Generative Models from Minimal Data

Abstract We propose a method for constructing generative models of 3D objects from a single 3D mesh and improving them through unsupervised low-shot learning from 2D images. Our method produces a 3D morphable model that represents shape and albedo in terms of Gaussian processes. Whereas...

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Bibliographic Details
Main Authors: Sutherland, Skylar, Egger, Bernhard, Tenenbaum, Joshua
Other Authors: Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Format: Article
Language:English
Published: Springer US 2023
Online Access:https://hdl.handle.net/1721.1/152192

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