Leveraging Vision Reconstruction Pipelines for Satellite Imagery
This addresses the challenge of adapting vision methods for remote sensing applications, but it is incremental as it applies existing techniques to a new domain.
The paper tackled the problem of 3D reconstruction from satellite imagery by applying state-of-the-art computer vision pipelines, showing that they offer competitive speed and accuracy in this context.
Reconstructing 3D geometry from satellite imagery is an important topic of research. However, disparities exist between how this 3D reconstruction problem is handled in the remote sensing context and how multi-view reconstruction pipelines have been developed in the computer vision community. In this paper, we explore whether state-of-the-art reconstruction pipelines from the vision community can be applied to the satellite imagery. Along the way, we address several challenges adapting vision-based structure from motion and multi-view stereo methods. We show that vision pipelines can offer competitive speed and accuracy in the satellite context.