Tuesday, May 19, 2020. 12:00 PM. Link to Zoom for Online Seminar.

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Laura Leal-Taixe -- Multi-Object Tracking: Towards end-to-end learning and data privacy.

Abstract: In this talk, I will go over two of our recent works in multi-object tracking that aim to push the field towards the end-to-end learning paradigm. In the first one, we study the power of using the regression head of the detector for tracking, hence converting a detector into a tracktor. Even if this approach yields state-of-the-art results, it has obvious shortcomings which we analyze and aim to overcome in the second work. Towards this end, we leverage the graphical model formulation of multi-object tracking in order to cast the tracking problem as an end-to-end learning problem. I would also like to talk about a brand new aspect of multi-object tracking that we are working on, one which we foresee will have a strong impact in the way the field is applied to society, namely, data privacy.

Bio: Prof. Dr. Laura Leal-Taixe is a tenure-track professor (W2) at the Technical University of Munich, leading the Dynamic Vision and Learning group. Before that, she spent two years as a postdoctoral researcher at ETH Zurich, Switzerland, and a year as a senior postdoctoral researcher in the Computer Vision Group at the Technical University in Munich. She obtained her PhD from the Leibniz University of Hannover in Germany, spending a year as a visiting scholar at the University of Michigan, Ann Arbor, USA. She pursued B.Sc. and M.Sc. in Telecommunications Engineering at the Technical University of Catalonia (UPC) in her native city of Barcelona. She went to Boston, USA to do her Masters Thesis at Northeastern University with a fellowship from the Vodafone foundation. She is a recipient of the Sofja Kovalevskaja Award of 1.65 million euros for her project socialMaps.