GAMES Webinar 2019 – 111期(Geometric Deep Learning 专题进展报告) | Maks Ovsjanikov(Ecole Polytechnique)

【GAMES Webinar 2019-111期】


报告嘉宾:Maks Ovsjanikov,Ecole Polytechnique

报告时间:2019年9月19日 晚8:00-9:30(北京时间)

报告题目:Some recent methods in non-rigid shape matching, with and without learning


In this talk, I will describe several methods for non-rigid shape matching, exploiting both geometric and learning-based techniques. My main goal will be to show that these two classes can often “communicate” very effectively, in both the supervised and unsupervised settings.


Maks Ovsjanikov is a Professor at Ecole Polytechnique in France. He received his PhD from Stanford University with an Excellence in Research Award from the Institute for Computational and Mathematical Engineering. He was a recipient of the Eurographics Young Researcher Award in 2014 “in recognition of his outstanding contributions to theoretical foundations of non-rigid shape matching”. In 2017 he received an ERC Starting Grant from the European Commission and a Bronze Medal from the French National Center for Scientific Research (CNRS) in 2018. He works on 3D shape analysis with emphasis on shape matching and correspondence.



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