The goal of this internship is to investigate advanced methods for fusing complementary information from cameras and radars to achieve a robust and accurate 3D understanding of the driving environment (3d detection, 3d semantic segmentation...). Cameras provide rich semantic and structural cues for object recognition and scene interpretation, while radars deliver precise range and velocity measurements that remain reliable under adverse weather and lighting conditions. By combining these modalities, the intern will explore novel deep learning architectures for multi-sensor fusion, with the aim of improving accuracy in complex driving scenarios.

To achieve these objectives, the intern will be expected to:
- Review the state of the art on camera-radar fusion for 3D perception
- Design, develop and evaluate a novel deep learning models for multi-sensor fusion
- Contribute to research reports and potential publications

https://kalisteo.cea.fr/wp-content/uploads/2025/09/S03_short_radar.pdf

Conformément aux engagements pris par le CEA en faveur de l'intégration des personnes handicapées, cet emploi est ouvert à toutes et à tous. Le CEA propose des aménagements et/ou des possibilités d'organisation pour l'inclusion des travailleurs handicapés.