Pia Bideau

Pia Bideau
Postdoctoral Researcher Science of Intelligence Technical University Berlin Email: p.bideau AT tu-berlin.de google scholar

About Me

I am a Postdoctoral Researcher at TU Berlin and part of the research cluster Science of Intelligence and the RBO lab. My research lies at the intersection of computer vision and robotics. Personally, I am interested in developing visual intelligence that allows agents to perceive and understand their environment. To this end, my work makes use of known physical information about the real world to enable learning systems to tackle changes and variation in the environment, while minimizing human supervision. Thinking of future, I am hoping agents will be able to safely interact with their environment and peers.

In December 2019 I graduated from University of Massachusetts, Amherst, where I was lucky to be advised by Prof. Erik Learned-Miller. In 2018 I did an internship at INRIA, Grenoble working with Karteek Alahari and Cordelia Schmid. I got my M.Sc degree from Ruhr-University Bochum.

"Man muss das Unmögliche versuchen, um das Mögliche zu erreichen." - (Hermann Hesse) "You must try the impossible to reach the possible." - (Hermann Hesse)

News

The first SCIoI Summer School on Embodied Intelligence - Perception and Learning in Nature and Robotics is taking place in Berlin.
Please checkout our Workshop at ECCV 2022 "What is motion for?"
New paper accepted at ECCV 2022 - Congratulations Marah Halawa!

Publications

	New "Action-based Contrastive Learning for Trajectory Prediction" Marah Halawa, Olaf Hellwich, Pia Bideau, in ECCV, 2022 paper

	"The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data" Cheng Gu, Erik Learned-Miller, Daniel Sheldon, Guillermo Gallego, Pia Bideau, in ICCV, 2021 project page code

	"C-14: Assured Timestamps for Drone Videos" Zhipeng Tang, Fabien Delattre, Pia Bideau, Mark D. Corner, Erik Learned-Miller, in The 26th Annual International Conference on Mobile Computing and Networking (MobiCom), 2020 paper

	Best workshop paper "MoA-Net: Self-Supervised Motion Segmentation" Pia Bideau, Rakesh Menon, Erik Learned-Miller, in ECCV workshop: what is optical flow for?, 2018 paper slides (pdf)

	"The best of both worlds: Combining CNNs and geometric constraints for hierarchichal motion segmentation" Pia Bideau, Aruni RoyChowdhury, Rakesh Menon, Erik Learned-Miller, in CVPR, 2018 project page code evaluation code

	"A Detailed Rubric for Motion Segmentation" Pia Bideau, Erik Learned-Miller, ArXiv preprint, 2016 project page

	"It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos" Pia Bideau, Erik Learned-Miller, in ECCV, 2016 project page

Teaching

X-Student Research Group
Active Perception - estimating depth from motion, WS22/23

course website NEWs

Presentations

01/25/2023	"Learning for and from motion" Scientific Symposium - Max Planck Institut for Intelligent Systems, Stuttgart symposium schedule
06/22/2021	"Different representations of motion information - and what can we learn from those?" Robotics Colloquium - Learning and Intelligent Systems Lab, TU Berlin youTube
09/14/2018	"MoA-Net: Self-Supervised Motion Segmentation" Pia Bideau, Rakesh R Menon, Erik Learned-Miller, Workshop: What is optical flow for?, ECCV2018 slides with example videos slides (pdf)
10/10/2016	"Causal Motion Segmentation in Moving Camera Videos" Pia Bideau, Erik Learned-Miller, The Second International Workshop on Video Segmentation, ECCV2016 slides with example videos slides (pdf)