Abstract
On Expressive Shape Representations from Generative Models to 3D Deep Learning
Ilke Demir (GL)
Intel Research
This talk will discuss and present a collection of approaches to extract and utilize several shape representations. We will start with building hiearchical and parametrized shape representations (grammars) from several shape formats, then explore their use cases for generative models, and continue with how similar constructions can be exploited in extracting shape abstractions in the context of 3D deep learning.
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