The 2019 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), the Johns Hopkins University (JHU), and the Intelligence Advanced Research Projects Activity (IARPA), aimed to promote research in semantic 3D reconstruction and stereo using machine intelligence and deep learning applied to satellite images.
The 2017 IEEE GRSS Data Fusion Contest, organized by the IEEE GRSS Image Analysis and Data Fusion Technical Committee, aimed at promoting progress on fusion and analysis methodologies for multisource remote sensing data.
The 2016 IEEE GRSS Data Fusion Contest, organized by the IEEE GRSS Image Analysis and Data Fusion Technical Committee, aimed at promoting progress on fusion and analysis methodologies for multisource remote sensing data.
New multi-source, multi-temporal data including Very High Resolution (VHR) multi-temporal imagery and video from space were released. First, VHR images (DEIMOS-2 standard products) acquired at two different dates, before and after orthorectification:
We introduce a new robotic RGBD dataset with difficult luminosity conditions: ONERA.ROOM. It comprises RGB-D data (as pairs of images) and corresponding annotations in PASCAL VOC format (xml files)
It aims at People detection, in (mostly) indoor and outdoor environments. People in the field of view can be standing, but also lying on the ground as after a fall.
The Onera Satellite Change Detection dataset addresses the issue of detecting changes between satellite images from different dates.