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Pia Bideau

Lupe

Telephone: +49.30.314-75857

Research Interests

I'm a postdoctoral researcher at TU Berlin and part of the Cluster Science of Intelligence as well as the RBO lab. I in particular like research at the intersection of Computer Vision, Robotics and Machine learning.

Before joining the Cluster of Intelligence, I did my PhD at University of Massachusetts, Amherst (USA) working with Prof. Erik Learned-Miller.  During my PhD I had the opportunity to work together with Cordelia Schmid and Karteek Alahari as part of an internship at Inria in Grenoble (France) what was a lot of fun. I got my M.Sc. in Electrical Engineering and Information Technology from Ruhr-University Bochum.

In my thesis I developed new methods for moving object segmentation in unconstrained videos. Motion is a key ability that we as living beings have to explore our environment. Our motion for example helps us to perceive depth, and the motion of objects helps us to recognize these objects even if those are unknown to us. In general my research aims at the following questions, how can we incorporate physical principles into vision systems? And how can we adopt learned principles to a never previously seen scenario? Creating this kind of common sense understanding for machines requires consideration of many different aspects (physics of the world, social interactions, cultural background, etc.). To me, especially this makes the intersection between computer vision and robotics an incredible challenging but also very interesting research area to explore.

 

 

Publications

Zhipeng Tang, Fabien Delattre, Pia Bideau, Mark D Corner, Erik Learned-Miller 2020. C-14: assured timestamps for drone videos. Proceedings of the 26th Annual International Conference on Mobile Computing and Networking, 1-13..


Pia Bideau, Erik Learned-Miller 2016. It’s moving! A probabilistic model for causal motion segmentation in moving camera videos. European Conference on Computer Vision, 433-449..


Pia Bideau, Aruni RoyChowdhury, Rakesh R Menon, Erik Learned-Miller 2018. The best of both worlds: Combining cnns and geometric constraints for hierarchical motion segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 508-517..


Pia Bideau, Erik Learned-Miller 2016. A detailed rubric for motion segmentation. arXiv preprint arXiv:1610.10033


Pia Bideau, Rakesh R Menon, Erik Learned-Miller 2018. MoA-Net: self-supervised motion segmentation. Proceedings of the European Conference on Computer Vision (ECCV) Workshops.



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Xenia Thau
Tel. +49 30 314-73 110
Fax +49 30 314-21 116
Room MAR 5.032

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TU Berlin
Fakultät IV, MAR 5-1
Marchstraße 23
10587 Berlin
Germany