Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label Prediction. - Charles Corbière; Hédi Ben-Younes; Alexandre Ramé; Charles Ollion (ICCV Workshops, 2017)

Addressing Failure Prediction by Learning Model Confidence. - Charles Corbière; Nicolas Thome; Avner Bar-Hen; Matthieu Cord; Patrick Pérez (NeurIPS, 2019)

Take One Gram of Neural Features, Get Enhanced Group Robustness. - Simon Roburin; Charles Corbière; Gilles Puy; Nicolas Thome; Mathieu Aubry; Renaud Marlet; Patrick Pérez (CoRR, 2022)

Robust Deep Learning for Autonomous Driving. - Charles Corbière (CoRR, 2022)

Confidence Estimation via Auxiliary Models. - Charles Corbière; Nicolas Thome; Antoine Saporta; Tuan-Hung Vu; Matthieu Cord; Patrick Pérez (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Apprentissage profond robuste pour la conduite autonome. (Robust deep learning for autonomous driving). - Charles Corbière (2022)

HELVIPAD: A Real-World Dataset for Omnidirectional Stereo Depth Estimation. - Mehdi Zayene; Jannik Endres; Albias Havolli; Charles Corbière; Salim Cherkaoui; Alexandre Kontouli; Alexandre Alahi (CVPR, 2025)

DRIVINGVQA: Analyzing Visual Chain-of-Thought Reasoning of Vision Language Models in Real-World Scenarios with Driving Theory Tests. - Charles Corbière; Simon Roburin; Syrielle Montariol; Antoine Bosselut; Alexandre Alahi (CoRR, 2025)

Boosting Omnidirectional Stereo Matching with a Pre-trained Depth Foundation Model. - Jannik Endres; Oliver Hahn 001; Charles Corbière; Simone Schaub-Meyer; Stefan Roth 001; Alexandre Alahi (CoRR, 2025)