Privileged Attribution Constrained Deep Networks for Facial Expression Recognition. - Jules Bonnard; Arnaud Dapogny; Ferdinand Dhombres; Kevin Bailly (ICPR, 2022)

Multi-Task Transformer with uncertainty modelling for Face Based Affective Computing. - Gauthier Tallec; Jules Bonnard; Arnaud Dapogny; Kévin Bailly (CoRR, 2022)

RULe: Relocalization-Uniformization-Landmark Estimation Network for Real-Time Face Alignment in Degraded Conditions. - Arnaud Dapogny; Gauthier Tallec; Jules Bonnard; Edouard Yvinec; Kévin Bailly (FG, 2023)

Adversarial Deep Multi-Task Learning Using Semantically Orthogonal Spaces and Application to Facial Attributes Prediction. - Arnaud Dapogny; Gauthier Tallec; Jules Bonnard; Edouard Yvinec; Kévin Bailly (FG, 2023)

Ontology-Guided Deep Metric Learning and Applications to Obstetrics. - Jules Bonnard; Arnaud Dapogny; Ferdinand Dhombres; Kévin Bailly (ICPR (9), 2024)

Machine learning for fetal ultrasound image analysis using privileged information. (Machine learning pour l'analyse d'échographies fœtales avec l'utilisation d'information privilégiée). - Jules Bonnard (2024)

Prior-Guided Attribution of Deep Neural Networks for Obstetrics and Gynecology. - Jules Bonnard; Arnaud Dapogny; Richard Zsamboki; Lucrezia De Braud; Davor Jurkovic; Kévin Bailly; Ferdinand Dhombres (IEEE J. Biomed. Health Informatics, 2024)