Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Geometric Disentanglement for Generative Latent Shape Models   Representing 3D shape is a fundamental problem in artificial intelligence,
which has numerous applications within computer vision and graphics. One avenue
that has recently begun to be explored is the use of latent representations of
generative models. However, it remains an open problem to learn a generative
model of shape that is interpretable and easily manipulated, particularly in
the absence of supervised labels. In this paper, we propose an unsupervised
approach to partitioning the latent space of a variational autoencoder for 3D
point clouds in a natural way, using only geometric information. Our method
makes use of tools from spectral differential geometry to separate intrinsic
and extrinsic shape information, and then considers several hierarchical
disentanglement penalties for dividing the latent space in this manner,
including a novel one that penalizes the Jacobian of the latent representation
of the decoded output with respect to the latent encoding. We show that the
resulting representation exhibits intuitive and interpretable behavior,
enabling tasks such as pose transfer and pose-aware shape retrieval that cannot
easily be performed by models with an entangled representation.

22
The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
14
The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom