Fabrizio Lande
Multimodal-source image generation with deep learning.
Rel. Paolo Garza, Erfan Ghaderey, Ruben Cartuyvels Cartuyvels. Politecnico di Torino, Master of science program in Data Science And Engineering, 2021
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Abstract
The focus of this work almost completely carried on during my stay at KU Leuven University as part of my Erasmus project, is to present a new way of synthesizing images starting from a descriptive input text and a reference image by using a model, RaGAN, extensively based on deep learning and generative adversarial network, that could set a base for future experimentation in this hybrid field that is multimodal source image generation.
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