Machine Learning for 3D Understanding
Time: July 2-4, 2018
Location: TUM Institute for Advanced Study, Lichtenbergstr. 2 a, 85748 Garching
3D understanding has been a topic of computer vision since the inception of the field. In the recent years, the interest in 3D understanding has been revived, fueled by the availability of affordable and compact 3D sensors as well as applications such as augmented reality and self-driving cars.
The dramatic success of deep learning in image analysis has brought a keen interest to apply similar methods to geometric 3D data. Many challenges arising from the unstructured and non-Euclidean nature of such data have to be addressed in order to develop successful geometric deep learning algorithms.
The goal of this workshop is to bring together the leading experts in computer vision, graphics, geometry, and machine learning, in order to foster collaboration and exchange of ideas across different areas. The workshop will not only present the current state-of-the-art in the field but also explore promising future research directions and open problems.