SGP 2020 Graduate School: Deep Learning for Geometric Data
Niloy Mitra and Paul Guerrero More details at In computer graphics, many traditional problems are now better handled by deeplearningbased datadriven methods. In an increasing variety of problem settings, deep networks are stateoftheart, beating dedicated handcrafted methods by significant margins. After reviewing relevant background from the regular imaging domain, in this tutorial, we will discuss the stateoftheart in terms of geometry and topology synthes
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