(2019) Garde Lecumberri, Gonzalo; Villanueva Larre, Arantxa; Escuela Técnica Superior de Ingenieros Industriales y de Telecomunicación; Telekomunikazio eta Industria Ingeniarien Goi Mailako Eskola Teknikoa
Every day, while developing applications and products to solve a huge number of
today problems, data from real world is registered and consumed. The registration of this
kind of data is costly, and on its quality depends on the correct behaviour of the solutions
developed. Some of this data are 2-dimensional point clouds, for example spatial points
registered by sensors. In this project, we present and investigate the use Generative
Adversarial Networks and Neural Style Transfer over 2-dimensional point clouds in order
to develop a tool to generate synthetic but realistic data based on real ones. We also
study the possibility of combining these two technologies to improve each other's
behaviour.