Pia Bideau

Pia Bideau

Researcher
INRIA Grenoble
MIAI, University Grenoble Alpes

Email: pia.bideau AT inria.fr
google scholar


About Me

I recently joint the THOTH team at INRIA and MIAI Grenoble Alpes as junior Research Chair for "Perception and Interaction". Before joining MIAI I was 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 February 2020 I graduated from University of Massachusetts, Amherst, where I was lucky to be advised by Prof. Erik Learned-Miller. I got my M.Sc degree in Electrical Engineering and Information Technolgy from Ruhr-University Bochum. After my Abitur in Germany I studied in a dual degree program that included a three year vocational education at Siemens as an Electrician for Automation Technology, - which brings me now back to exciting research at the edge between computer vision and robotics.

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


Hiring

I am looking for highly motivated PhD students (+internships) to join the team at INRIA. We have currently a few openings in the area of motion estimation and variational deep architectures for human-object interaction.

Please reach out by email if you're interested!

News

Publications

Learning Latent Behavior Representations


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

paper




"Knowledge-augmented face perception: Prospects for the Bayesian brain-framework to align AI and human vision
"
Martin Maier, Florian Blume, Pia Bideau, Olaf Hellwich, Rasha Abdel Rahman in Consciousness and Cognition, 2022

paper



Geometric Scene Understanding


"The Right Spin: Learning object Motion from Rotation-Compensated Flow Fields
"
Pia Bideau, Erik Learned-Miller, Cordelia Schmid, Karteek Alahari in International Journal of Computer Vision (IJCV), 2023

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 I - estimating depth from motion, WS22/23

course website NEWs


X-Student Research Group

Active Perception II - estimating depth from motion, SS23

course website


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)