students
PhD students, post-docs and interns I have (co-)supervised.
Ph.D. students
- Nicolas Sereyjol-Garros, at valeo.ai and ENPC, with Gilles Puy, Nermin Samet, Renaud Marlet and Vincent Lepetit
- Fatima Balde, 3D scene-level modeling from a single image, in ASTRA team (joint valeo.ai / Inria), with Raoul de Charette
- Tetiana Martyniuk, Conditional generation for urban scenes, in ASTRA team (joint valeo.ai / Inria), with Gilles Puy, Renaud Marlet and Raoul de Charette
Alumni
- Loick Chambon, Scene perception for autonomous driving, at valeo.ai and Sorbonne University, with Eloi Zablocki and Matthieu Cord
- Corentin Sautier, Self-supervised learning for 3D point clouds with multi-modal data, at valeo.ai and ENPC, with Gilles Puy, Renaud Marlet and Vincent Lepetit
- Björn Michele, Domain adaptation for 3D data, at valeo.ai and IRISA, with Gilles Puy, Renaud Marlet and Nicolas Courty
- Yuan Yin, post-doc, Adversarial trajectories for motion planners, at valeo.ai, with Eloi Zablocki
- Javiera Castillo Navarro, Ph.D. student, Semi-supervised semantic segmentation of large scale remote sensing data, at ONERA (DTIS/IVA) and IRISA, with Bertrand Le Saux and Sébastien Lefèvre
- Pierre-Alain Langlois, Ph.D. student, Geometric and semantic approaches for digital building model reconstruction, at ENPC (Imagine team), with Renaud Marlet
- Pierre Godet, Ph.D. student, Machine learning for multi-frame motion estimation in videos, at ONERA (DTIS/IVA), with Aurélien Plyer and Guy Le Besnerais. PhD January 2021.
- Rodrigo Caye Daudt, Ph.D. student, Deep learning for remote sensing multi-temporal image analysis, at ONERA (DTIS/IVA) and Télécom Paris (LTCI/IMAGES), with Bertrand Le Saux and Yann Gousseau. PhD November 2020.
Undergrad / MSc. students
- Luiz Felipe Nery: VLMs for driving, 2026, cosupervised with Monika Wysoczanska and Ellington Kirby
- Matteo Marengo: Urban scene reconstruction, 2024, cosupervised with Renaud Marlet and Raoul De Charette
- Achraff Adjileye: Motion forecasting with additional data, 2024, cosupervised with Yihong Xu
- Pegah Khayatan: Robustness and corner case generation for motion forecasting, 2023, cosupervised with Eloi Zablocki
- Sophia Sirko-Galouchenko: Self-supervision for camera-based bird’s-eye-view perception in autonomous driving, 2023, cosupervised with Spyros Gidaris and Andrei Bursuc
- Angelika Ando: Exploiting vision transformers for 3d semantic segmentation, 2022, cosupervised with Spyros Gidaris, Andrei Bursuc and Gilles Puy
- Loick Chambon: Multi-modal generation for 3D urban scenes, 2022, cosupervised with Mickael Chen, Tuan-Hung Vu and Andrei Bursuc
- Corentin Sautier: Self-supervision for point clouds, 2021, cosupervised with Gilles Puy, Renaud Marlet, Spyros Gidaris and Andreï Bursuc
- Anh Quan Cao: Scene Flow Estimation from 3D Lidar point cloud using deep learning, 2020, co-supervised with Gilles Puy and Renaud Marlet
- Björn Michele: Zero-shot learning for 3D data, 2020, co-supervised with Maxime Bucher, Renaud Marlet and Gilles Puy
- Jean-Lynce Gnanago: Deep learning TEC map prediction, 2018, co-supervised with Fabien Gachet
- Noellie Cherrier: Deep learning TEC map prediction, 2017, co-supervised with Thibault Castaings