FR3.R14.1: TOWARDS DIVERSE AND REPRESENTATIVE GLOBAL PRETRAINING DATASETS FOR REMOTE SENSING FOUNDATION MODELS
Jacob Arndt, Philipe Dias, Abhishek Potnis, Dalton Lunga, Oak Ridge National Laboratory, United States
FR3.R14.3: GEOBIND: BINDING TEXT, IMAGE, AND AUDIO THROUGH SATELLITE IMAGES
Aayush Dhakal, Subash Khanal, Srikumar Sastry, Adeel Ahmad, Nathan Jacobs, Washington University in Saint Louis, United States
FR3.R14.4: ONE FOR ALL: TOWARD UNIFIED FOUNDATION MODELS FOR EARTH VISION
Zhitong Xiong, Yi Wang, Fahong Zhang, Xiao Xiang Zhu, Technical University of Munich, Germany
FR3.R14.5: PhilEO Bench: Evaluating Geo-Spatial Foundation Models
Casper Fibaek, Luke Camilleri, European Space Agency (ESA), Italy; Andreas Luyts, VITO, Belgium; Nikolaos Dionelis, Bertrand Le Saux, European Space Agency (ESA), Italy
FR3.R14.6: TRAINING VISUAL LANGUAGE MODELS WITH OBJECT DETECTION: GROUNDED CHANGE DESCRIPTIONS IN SATELLITE IMAGES
João Luis Prado Vieira, Syrielle Montariol, Javiera Castillo Navarro, Devis Tuia, Antoine Bosselut, EPFL, Switzerland
FR3.R14.7: SEGMENTATION-GUIDED ATTENTION FOR VISUAL QUESTION ANSWERING FROM REMOTE SENSING IMAGES
Lucrezia Tosato, Hichem Boussaid, Université Paris Cité, France; Flora Weissgerber, ONERA, France; Camille Kurtz, Laurent Wendling, Sylvain Lobry, Université Paris Cité, France
