1 code implementation • CVPR 2020 • Jan Svoboda, Asha Anoosheh, Christian Osendorfer, Jonathan Masci
This paper introduces a neural style transfer model to generate a stylized image conditioning on a set of examples describing the desired style.
1 code implementation • ICLR 2019 • Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas Guibas
Deep learning systems have become ubiquitous in many aspects of our lives.
no code implementations • 4 May 2017 • Jan Svoboda, Federico Monti, Michael M. Bronstein
Performance of fingerprint recognition depends heavily on the extraction of minutiae points.
4 code implementations • CVPR 2017 • Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein
Recently, there has been an increasing interest in geometric deep learning, attempting to generalize deep learning methods to non-Euclidean structured data such as graphs and manifolds, with a variety of applications from the domains of network analysis, computational social science, or computer graphics.
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