Open Internship Proposals
We are looking for students finishing their MSc with a solid background in computer vision and machine learning, particularly in deep learning with strong PyTorch coding skills. Interns work on research topics, typically for 6 months (usually spring and summer), resulting for a great part in paper submissions to top-tier conferences. Some trainees go on to do a PhD thesis in the lab. We currently have four exciting internship opportunities for MSc students!
How to Apply
Send an email to the supervisors (one email per application) with the following:
- A cover letter explaining your interest and qualifications for the topic.
- Your CV/resume.
- Transcripts of your grades from last year (and this year, if available).
Available Topics:
Universal 2D-3D Transformer
Keywords: Transformer, Representation learning, Self-supervised learning, Multi-modal
Supervisors: Tuan-Hung Vu, Gilles Puy, Spyros Gidaris
This project aims to develop a novel transformer architecture capable of processing 2D and 3D data simultaneously, probing synergistic multi-modal representations between imagery and LiDAR data.
Learning from One Continuous Long-Range Video Stream
Keywords: Video understanding, Continual learning, Transformer, Self-supervised pretraining
Supervisors: Shashanka Venkataramanan, Andrei Bursuc
This internship involves building a video understanding model inspired by human episodic memory to learn continuously from long-range streams. It includes exploring continual learning, memory integration, and advanced pretraining techniques using real-world video datasets.
Scenario Generation for Robust Autonomous Driving using Diffusion Models
Keywords: Diffusion models, Long-tail distribution, Online mapping, Motion prediction
Supervisors: Yuan Yin, Yihong Xu
This internship explores using diffusion models to generate driving scenarios, focusing on map and trajectory creation. The goal is to develop robust, vector-based maps and diverse vehicle behaviors to enhance motion forecasting and planning.
Object Generation from Range Images
Keywords: Diffusion models, Point clouds, Controllable generative models
Supervisors: Nermin Samet, Victor Besnier
This project focuses on generating LiDAR point cloud objects by leveraging pre-trained diffusion models on range image representations. The goal is to improve the controllability of LiDAR object generation in a computationally efficient way.
Alumni interns and visiting students
Valentin Gerard - Internship 2024
Currently: PhD student at EPFL with Alexandre Alahi
Ellington Kirby - Internship 2024
Currently: Computer Vision engineer at Parrot
Matteo Marengo - Internship 2024
Currently: Research Intern at Harvard Medical School
Walter Simoncini - Visiting Master student (April 2024 - May 2024)
Currently: PhD student at University of Technology Nuremberg with Yuki Asano
Monika Wysoczanska - Visiting PhD student (July 2023 - June 2024)
Currently: Internship at Google Deepmind with Cordelia Schmid
Amaia Cardiel - Internship 2023
Currently: PhD student at Valeo.ai and Grenoble Université with Eric Gaussier
Sophia Sirko-Galouchenko - Internship 2023
Currently: PhD student at Valeo.ai and Sorbonne Université with Nicolas Thome
Pegah Khayatan - Internship 2023
Currently: Visiting student at Sorbonne Université with Matthieu Cord
Thibaut Loiseau - Internship 2023
Currently: PhD student at ENPC with Vincent Lepetit
Denis Mbey Akola - Internship 2023
Currently: PhD student at NYU with David Fouhey
Loïck Chambon - Internship 2022
Currently: PhD student at Valeo.ai and Sorbonne Université with Matthieu Cord
Mehdi Zemni - Internship 2022
Currently: Data scientist at Argon & co
Chloé Sekkat - Internship 2022
Currently: Machine Learning Engineer at Sonos
Victoria Brami - Internship 2022
Currently: Vision-LLM Engineer at Woven by Toyota
Angelika Ando - Internship 2022
Currently: PhD student in Mines wtih Fabien Moutarde and Bogdan Stanciulescu
Corentin Sautier - Internship 2021
Currently: PhD student at Valeo.ai and ENPC with Vincent Lepetit
Imen Maazoun - Internship 2021
Currently: Machine Learning Engineer at Monk AI
Paul Jacob - Internship 2021
Currently: Research scientist at Mistral AI. Previously Research scientist at Owkin
Anh-Quan Cao - Internship 2020
Currently: PhD student at INRIA with Raoul de Charette
Björn Michele - Internship 2020
Currently: PhD student at Valeo.ai and IRISA OBELIX with Nicolas Courty
Guillaume Le Moing - Internship 2020
Currently: Research scientist at Google Deepmind. PhD at INRIA with Jean Ponce and Cordelia Schmid
Victor Besnier - Internship 2019
Currently: Research scientist at valeo.ai. PhD at Valeo and ENPC with David Picard
Florent Bartoccioni - Internship 2019
Currently: Research engineer at valeo.ai. PhD at Valeo.ai and INRIA with Karteek Alahari.
Projects led or contributed to by interns
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Éloi Zablocki*, Valentin Gerard*, Amaia Cardiel, Eric Gaussier, Matthieu Cord, Eduardo Valle
under review, 2025
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Monika Wysoczańska, Antonin Vobecky, Amaia Cardiel, Tomasz Trzciński, Renaud Marlet, Andrei Bursuc, Oriane Siméoni
under review, 2025
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Walter Simoncini, Spyros Gidaris, Andrei Bursuc, Yuki M. Asano
NeurIPS, 2024
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Monika Wysoczańska, Oriane Siméoni, Michaël Ramamonjisoa, Andrei Bursuc, Tomasz Trzciński, Patrick Pérez
ECCV, 2024
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Thibaut Loiseau, Tuan-Hung Vu, Mickael Chen, Patrick Pérez, Matthieu Cord
ECCV, 2024
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Amaia Cardiel, Éloi Zablocki, Oriane Siméoni, Elias Ramzi, Matthieu Cord
ECCV Workshop EVAL-FoMo, 2024
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Yuan Yin, Pegah Khayatan, Éloi Zablocki, Alexandre Boulch, Matthieu Cord
ECCV Workshop W-CODA, 2024
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Sophia Sirko-Galouchenko, Alexandre Boulch, Spyros Gidaris, Andrei Bursuc, Antonin Vobecky, Patrick Pérez, Renaud Marlet
CVPR Workshop WAD, 2024
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Monika Wysoczańska, Michaël Ramamonjisoa, Tomasz Trzciński, Oriane Siméoni
WACV, 2024
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Oriane Siméoni, Chloé Sekkat, Gilles Puy, Antonin Vobecky, Éloi Zablocki, Patrick Pérez
CVPR, 2023
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Mehdi Zemni, Mickaël Chen, Éloi Zablocki, Hédi Ben-Younes, Patrick Pérez, Matthieu Cord
CVPR, 2023
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Loïck Chambon, Mickaël Chen, Tuan-Hung Vu, Alexandre Boulch, Andrei Bursuc, Matthieu Cord, Patrick Pérez
NeurIPS ML4AD Workshop, 2022
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Paul Jacob, Éloi Zablocki, Hédi Ben-Younes, Mickaël Chen, Patrick Pérez, Matthieu Cord
ECCV, 2022
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Corentin Sautier, Gilles Puy, Spyros Gidaris, Alexandre Boulch, Andrei Bursuc, and Renaud Marlet
CVPR, 2022
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Bjoern Michele, Alexandre Boulch, Gilles Puy, Maxime Bucher, and Renaud Marlet
3DV, 2021
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Anh-Quan Cao, Gilles Puy, Alexandre Boulch, and Renaud Marlet
ICCV, 2021
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Guillaume Le Moing, Tuan-Hung Vu, Himalaya Jain, Patrick Pérez and Matthieu Cord
CVPR, 2021