Foundation models

Foundation models break free from predefined and restricted ontologies, enabling them to perceive a wider range of elements in their surroundings. By pretraining these foundation models in an unsupervised way, we can adapt them to a diverse set of tasks.

Selected publications

  1. Fine-Tuning CLIP's Last Visual Projector: A Few-Shot Cornucopia
    Mohammad Fahes, Tuan-Hung Vu, Andrei Bursuc, Patrick Pérez, Raoul de Charette
    under review, 2025
    pdf Code
  2. Test-Time Contrastive Concepts for Open-World Semantic Segmentation
    Monika Wysoczańska, Antonin Vobecky, Amaia Cardiel, Tomasz Trzciński, Renaud Marlet, Andrei Bursuc, Oriane Siméoni
    under review, 2025
    pdf
  3. The BRAVO Semantic Segmentation Challenge Results in UNCV2024
    Tuan-Hung Vu, Eduardo Valle, Andrei Bursuc, Tommie Kerssies, Daan de Geus, Gijs Dubbelman, Long Qian, Bingke Zhu, Yingying Chen, Ming Tang, Jinqiao Wang, Tomáš Vojíř, Jan Šochman, Jiří Matas, Michael Smith, Frank Ferrie, Shamik Basu, Christos Sakaridis, Luc Van Gool
    European Conference on Computer Vision, 2024
    pdf Code
  4. Reliability in Semantic Segmentation: Can We Use Synthetic Data?
    Thibaut Loiseau, Tuan-Hung Vu, Mickael Chen, Patrick Pérez, Matthieu Cord
    European Conference on Computer Vision, 2024
    pdf Code
  5. LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Foundation Models
    Amaia Cardiel, Éloi Zablocki, Oriane Siméoni, Elias Ramzi, Matthieu Cord
    ECCV Workshop Emergent Visual Abilities and Limits of Foundation Models (EVAL-FoMo), 2024
    pdf
  6. UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction
    Lan Feng, Mohammadhossein Bahari, Kaouther Messaoud Ben Amor, Éloi Zablocki, Matthieu Cord, Alexandre Alahi
    European Conference on Computer Vision, 2024
    pdf Code
  7. A Simple Recipe for Language-guided Domain Generalized Segmentation
    Mohammad Fahes, Tuan-Hung Vu, Andrei Bursuc, Patrick Pérez, Raoul de Charette
    Computer Vision and Pattern Recognition, 2024
    pdf Code
  8. OccFeat: Self-supervised Occupancy Feature Prediction for Pretraining BEV Segmentation Networks
    Sophia Sirko-Galouchenko, Alexandre Boulch, Spyros Gidaris, Andrei Bursuc, Antonin Vobecky, Patrick Pérez, Renaud Marlet
    CVPR Workshop on Autonomous Driving (WAD), 2024
    pdf Code
  9. Three Pillars improving Vision Foundation Model Distillation for Lidar
    Gilles Puy, Spyros Gidaris, Alexandre Boulch, Oriane Siméoni, Corentin Sautier, Patrick Pérez, Andrei Bursuc, Renaud Marlet
    Computer Vision and Pattern Recognition, 2024
    pdf Code
  10. BEVContrast: Self-Supervision in BEV Space for Automotive Lidar Point Clouds
    Corentin Sautier, Gilles Puy, Alexandre Boulch, Renaud Marlet, Vincent Lepetit
    International Conference on 3D Vision (3DV), 2024
    pdf Code
  11. MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
    Spyros Gidaris, Andrei Bursuc, Oriane Siméoni, Nikos Komodakis, Matthieu Cord, Patrick Pérez
    Transactions on Machine Learning Research (TMLR), 2024
    pdf
  12. POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images
    Antonin Vobecky, Oriane Siméoni, David Hurych, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Josef Sivic
    Advances in Neural Information Processing Systems (NeurIPS), 2023
    pdf Code
  13. PØDA: Prompt-driven Zero-shot Domain Adaptation
    Mohammad Fahes, Tuan-Hung Vu, Andrei Bursuc, Patrick Pérez, Raoul de Charette
    International Conference on Computer Vision (ICCV), 2023
    pdf Code
  14. ALSO: Automotive Lidar Self-supervision by Occupancy estimation
    Alexandre Boulch, Corentin Sautier, Björn Michele, Gilles Puy, Renaud Marlet
    Computer Vision and Pattern Recognition, 2023
    pdf Code
  15. What to Hide from Your Students: Attention-Guided Masked Image Modeling
    Ioannis Kakogeorgiou, Spyros Gidaris, Bill Psomas, Yannis Avrithis, Andrei Bursuc, Konstantinos Karantzalos, and Nikos Komodakis
    European Conference on Computer Vision (ECCV), 2022
    pdf Code
  16. Online Bag-of-Visual-Words Generation for Unsupervised Representation Learning
    Spyros Gidaris, Andrei Bursuc, Gilles Puy, Nikos Komodakis, Patrick Pérez, and Matthieu Cord
    Computer Vision and Pattern Recognition, 2021
    pdf Code
  17. Learning Representations by Predicting Bags of Visual Words
    Spyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, and Matthieu Cord
    Computer Vision and Pattern Recognition, 2020
    pdf Code