Jaime's Sucessful Msc Thesis Defense
Congrats to Jaime for successfully defending his MSC thesis on "Towards Learning of a Joint Geometry-Structure Manifold for Shape Exploration"!
Here is the abstract of his thesis.
We present a first attempt at producing a continuous generative model of 3D objects from a joint representation that incorporates the discrete structural variability as well as the continuous geometric variability that are often present in collections of man-made shapes. Starting from a set of compatibly segmented shapes, our main contribution consists in demonstrating the construction of the joint representation. Then, by using Gaussian Process learning to produce a predictive manifold from the joint representation, we investigate its capabilities and limitations for reproducing and synthesizing new shapes.