Pia Bideau

Pia Bideau
Researcher INRIA Grenoble MIAI, University Grenoble Alpes Email: pia.bideau AT inria.fr google scholar

About Me

I recently joined 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 Technology 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 an opening for Anticipating Human Behavior for Human-Robot Interaction.

Please reach out by email or apply directly if you're interested!

News

[June'24] Two interesting workshop papers accepted at CVPR with oral presentations! A heartfelt thanks to the amazing co-authors who contributed their expertise in collective animal behavior and cognitive psychology.
- 🐟 🐟 Watching Swarm Dynamics from Above 🐟 🐟 at CV4Animals and,
- 😀 😮 Multi-Task Multi-Modal Self-supervised Learning for Facial Expression Recognition 😏 😲 at ABAW.
[Aug.'23] The first SCIoI Summer School on Embodied Intelligence - Perception and Learning in Nature and Robotics is taking place in Berlin.
[Sept.'22] Please checkout our Workshop at ECCV 2022 "What is motion for?"
[Sept.'22] New paper accepted at ECCV 2022 - Congratulations Marah Halawa!

Publications

Learning Latent Behavior Representations

	"How Do You Perceive My Face? Recognizing Facial Expressions in Multi-Modal Context by Modeling Mental Representations" Florian Blume, Runfeng Qu, Pia Bideau, Martin Maier, Rasha Abdel-Rahman, Olaf Hellwich in GCPR, 2024

	Oral presentation "Multi-Task Multi-Modal Self-Supervised Learning for Facial Expression Recognition" Marah Halawa, Florian Blume, Pia Bideau, Martin Maier, Rasha Abdel-Rahman, Olaf Hellwich in CVPRW, 2024 paper code

	"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

Computer Vision and Robotics in the Natural Sciences

Oral presentation
"Watching Swarm Dynamics from Above: A Framework for Advanced Object tracking in Drone Videos"
Duc Pham, Matthew Hansen, Félicie Dhellemmes, Jens Krause, Pia Bideau at CVPR in the workshop CV4Animals, 2024

paper

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
	"Model AI Assignment: Collective Intelligence from a Synthetic and Biological Perspective" Pia Bideau, David Bierbach, Wolfgang Hönig accepted at Symposium on Educational Advances in Artificial Intelligence (EAAI), 2024

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)