Deep understanding of mesh geometries for shape design

Point clouds and meshes (triangular, quadrilateral,...) are used to
model and to represent three-dimensional objects. Obtaining suitable
mesh representations and working with them in various applications
requires geometric knowledge of surface and shape properties. Recently
deep learning methods have been developed to achieve such tasks and the
new field of geometric deep learning has emerged.

In this seminar, papers from the field of geometric deep learning are
discussed as well as papers focusing on geometric properties needed for
example in architecture or fabrication of auxetic material that gives
predefined shapes from planar sheets.

Selected References for the seminar:


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