Multimodal Object Detection in Remote Sensing

Abdelbadie Belmouhcine (1) , Jean-Christophe Burnel (1) , Luc Courtrai (1) , Minh-Tan Pham (1) , Sébastien Lefèvre (1)

1 OBELIX - Observation de l’environnement par imagerie complexe

Object detection in remote sensing is a crucial computer vision task that has seen significant advancements with deep learning techniques. However, most existing works in this area focus on the use of generic object detection and do not leverage the potential of multimodal data fusion. In this paper, we present a comparison of methods for multimodal object detection in remote sensing, survey available multimodal datasets suitable for evaluation, and discuss future directions.

Keywords: Object Detection Remote Sensing Multimodality YOLOrs SuperYOLO; Object Detection; Remote Sensing; Multimodality; YOLOrs; SuperYOLO

Domains: Computer Vision and Pattern Recognition [cs.CV]

Abdelbadie Belmouhcine, Jean-Christophe Burnel, Luc Courtrai, Minh-Tan Pham, Sébastien Lefèvre. Multimodal Object Detection in Remote Sensing. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Jul 2023, Pasadena, France. pp.1245-1248, ⟨10.1109/IGARSS52108.2023.10281486⟩. ⟨hal-04430694⟩