6 papers
CrossEarth-SAR: A SAR-Centric and Billion-Scale Geospatial Foundation Model for Domain Generalizable Semantic Segmentation
Ziqi Ye, Ziyang Gong, Ning Liao +10
Synthetic Aperture Radar (SAR) enables global, all-weather earth observation. However, owing to diverse imaging mechanisms, domain shifts across sensors and regions severely hinder…
Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency Adaptation
Xiaoxing Hu, Ziyang Gong, Yupei Wang +8
Parameter-Efficient Fine-Tuning (PEFT) is a technique that allows us to adapt powerful Foundation Models (FMs) to diverse downstream tasks while preserving and unleashing their inh…
CrossEarth: Geospatial Vision Foundation Model for Domain Generalizable Remote Sensing Semantic Segmentation
Ziyang Gong, Zhixiang Wei, Di Wang +13
The field of Remote Sensing Domain Generalization (RSDG) has emerged as a critical and valuable research frontier, focusing on developing models that generalize effectively across…
Can Generative Geospatial Diffusion Models Excel as Discriminative Geospatial Foundation Models?
Yuru Jia, Valerio Marsocci, Ziyang Gong +3
Self-supervised learning (SSL) has revolutionized representation learning in Remote Sensing (RS), advancing Geospatial Foundation Models (GFMs) to leverage vast unlabeled satellite…
PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models
Valerio Marsocci, Yuru Jia, Georges Le Bellier +12
Geospatial Foundation Models (GFMs) have emerged as powerful tools for extracting representations from Earth observation data, but their evaluation remains inconsistent and narrow.…
COP-GEN-Beta: Unified Generative Modelling of COPernicus Imagery Thumbnails
Miguel Espinosa, Valerio Marsocci, Yuru Jia +2
In remote sensing, multi-modal data from various sensors capturing the same scene offers rich opportunities, but learning a unified representation across these modalities remains a…