2pm - 3pm
Wednesday 24 March 2021
Robust learning-based methods for shape correspondence
Dr Maks Ovsjanikov, Ecole Polytechnique, France will be speaking.
All are welcome!
Free
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Speakers
- Dr Maks Ovsjanikov
Short biography
I am a professor of computer science at Ecole Polytechnique. Prior to this, I worked for Google in their Image Search team in sunny Mountain View. In 2011 I graduated from with a Ph.D. in Computational Mathematics (from the ), having done work on shape analysis in the headed by prof. . In 2014, I received the . In 2018, I received a . My CV from October 2018 can be found .
Abstract
In this talk I will describe several recent works aimed at developing accurate and robust methods for non-rigid 3D shape matching and comparison. I will first describe several ways to model this problem, including supervised, unsupervised and weakly supervised training losses. In addition, I will highlight several recent architectures, focusing especially on spectral methods, that are well adapted to computing dense correspondences across a variety of settings. My ultimate goal will be to show that these techniques are becoming remarkably robust and universally applicable and useful.