Quentin Bouniot

According to our database, Quentin Bouniot authored at least 23 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling.

Ali Keshavarzi, Quentin Bouniot, Benjamin M. Smith, Elsa D. Angelini

CoRR, April, 2026

The Latent Color Subspace: Emergent Order in High-Dimensional Chaos.

Mateusz Pach, Jessica Bader, Quentin Bouniot, Serge J. Belongie, Zeynep Akata

CoRR, March, 2026

UNBOX: Unveiling Black-box visual models with Natural-language.

Simone Carnemolla, Chiara Maria Russo, Simone Palazzo, Quentin Bouniot, Daniela Giordano, Zeynep Akata, Matteo Pennisi, Concetto Spampinato

CoRR, March, 2026

Rethinking Concept Bottleneck Models: From Pitfalls to Solutions.

Merve Tapli, Quentin Bouniot, Wolfgang Stammer, Zeynep Akata, Emre Akbas

CoRR, March, 2026

SOTAlign: Semi-Supervised Alignment of Unimodal Vision and Language Models via Optimal Transport.

Simon Roschmann, Paul Krzakala, Sonia Mazelet, Quentin Bouniot, Zeynep Akata

CoRR, February, 2026

Dissecting Multimodal In-Context Learning: Modality Asymmetries and Circuit Dynamics in modern Transformers.

Yiran Huang, Karsten Roth, Quentin Bouniot, Wenjia Xu, Zeynep Akata

CoRR, January, 2026

TimeSAE: Sparse Decoding for Faithful Explanations of Black-Box Time Series Models.

Khalid Oublal, Quentin Bouniot, Qi Gan, Stéphan Clémençon, Zeynep Akata

CoRR, January, 2026

2025

Time Series Representations for Classification Lie Hidden in Pretrained Vision Transformers.

Simon Roschmann, Quentin Bouniot, Vasilii Feofanov, Ievgen Redko, Zeynep Akata

CoRR, June, 2025

Sparse Autoencoders Learn Monosemantic Features in Vision-Language Models.

Mateusz Pach, Shyamgopal Karthik, Quentin Bouniot, Serge J. Belongie, Zeynep Akata

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Restyling Unsupervised Concept Based Interpretable Networks with Generative Models.

Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d'Alché-Buc

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Tailoring Mixup to Data for Calibration.

Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport.

Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Oliver Struckmeier, Karol Arndt, Markus Heinonen, Ville Kyrki, Samuel Kaski

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2023

Towards Few-Annotation Learning in Computer Vision: Application to Image Classification and Object Detection tasks. (Vers un Apprentissage avec peu d'annotations en Vision par Ordinateur : Application aux tâches de classification d'images et de détection d'objets).

Quentin Bouniot

PhD thesis, 2023

Towards Few-Annotation Learning in Computer Vision: Application to Image Classification and Object Detection tasks.

Quentin Bouniot

CoRR, 2023

Tailoring Mixup to Data using Kernel Warping functions.

Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc

CoRR, 2023

Understanding deep neural networks through the lens of their non-linearity.

Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Karol Arndt, Oliver Struckmeier, Markus Heinonen, Ville Kyrki, Samuel Kaski

CoRR, 2023

Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient?

Quentin Bouniot, Angélique Loesch, Amaury Habrard, Romaric Audigier

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Proposal-Contrastive Pretraining for Object Detection from Fewer Data.

Quentin Bouniot, Romaric Audigier, Angélique Loesch, Amaury Habrard

Proceedings of the Eleventh International Conference on Learning Representations, 2023

The Robust Semantic Segmentation UNCV2023 Challenge Results.

Xuanlong Yu, Yi Zuo, Zitao Wang, Xiaowen Zhang, Jiaxuan Zhao, Yuting Yang, Licheng Jiao, Rui Peng, Xinyi Wang, Junpei Zhang, Kexin Zhang, Fang Liu, Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-Viñolo, Hanlin Tian, Kenta Matsui, Tianhao Wang, Fahmy Adan, Zhitong Gao, Xuming He, Quentin Bouniot, Hossein Moghaddam, Shyam Nandan Rai, Fabio Cermelli, Carlo Masone, Andrea Pilzer, Elisa Ricci, Andrei Bursuc, Arno Solin, Martin Trapp, Rui Li, Angela Yao, Wenlong Chen, Ivor Simpson, Neill D. F. Campbell, Gianni Franchi

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Improving Few-Shot Learning Through Multi-task Representation Learning Theory.

Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard

Proceedings of the Computer Vision - ECCV 2022, 2022

2020

Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms.

Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard

CoRR, 2020

Optimal Transport as a Defense Against Adversarial Attacks.

Quentin Bouniot, Romaric Audigier, Angelique Loesch

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Vulnerability of Person Re-Identification Models to Metric Adversarial Attacks.

Quentin Bouniot, Romaric Audigier, Angélique Loesch

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020