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Quentin Bouniot
Quentin Bouniot
Télécom Paris
Verified email at telecom-paris.fr - Homepage
Title
Cited by
Cited by
Year
Vulnerability of person re-identification models to metric adversarial attacks
Q Bouniot, R Audigier, A Loesch
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
232020
Optimal transport as a defense against adversarial attacks
Q Bouniot, R Audigier, A Loesch
2020 25th International Conference on Pattern Recognition (ICPR), 5044-5051, 2021
82021
Improving few-shot learning through multi-task representation learning theory
Q Bouniot, I Redko, R Audigier, A Loesch, A Habrard
European Conference on Computer Vision, 435-452, 2022
72022
Towards few-annotation learning for object detection: are transformer-based models more efficient?
Q Bouniot, A Loesch, R Audigier, A Habrard
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023
52023
Towards better understanding meta-learning methods through multi-task representation learning theory
Q Bouniot, I Redko, R Audigier, A Loesch, Y Zotkin, A Habrard
arXiv preprint arXiv:2010.01992, 2020
52020
Tailoring Mixup to Data using Kernel Warping functions
Q Bouniot, P Mozharovskyi, F d'Alché-Buc
arXiv preprint arXiv:2311.01434, 2023
12023
Proposal-contrastive pretraining for object detection from fewer data
Q Bouniot, R Audigier, A Loesch, A Habrard
arXiv preprint arXiv:2310.16835, 2023
12023
Towards Few-Annotation Learning in Computer Vision: Application to Image Classification and Object Detection tasks
Q Bouniot
arXiv preprint arXiv:2311.04888, 2023
2023
Understanding deep neural networks through the lens of their non-linearity
Q Bouniot, I Redko, A Mallasto, C Laclau, K Arndt, O Struckmeier, ...
arXiv preprint arXiv:2310.11439, 2023
2023
Towards Few-Annotation Learning in Computer Vision: Application to Image Classification and Object Detection tasks| Theses. fr
Q Bouniot
Saint-Etienne, 2023
2023
The Robust Semantic Segmentation UNCV2023 Challenge Results
X Yu, Y Zuo, Z Wang, X Zhang, J Zhao, Y Yang, L Jiao, R Peng, X Wang, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
2023
Understanding Few-Shot Multi-Task Representation Learning Theory
Q Bouniot, I Redko
ICLR Blog Track, 2022
2022
Vers une meilleure compréhension des méthodes de méta-apprentissage à travers la théorie de l’apprentissage de représentations multi-tâches
Q Bouniot, I Redko, R Audigier, A Loesch
2021
Putting theory to work: from learning bounds to meta-learning algorithms
Q Bouniot, I Redko, R Audigier, A Loesch, A Habrard
2020
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