3 papers
cs.CV2026
GroundSet: A Cadastral-Grounded Dataset for Spatial Understanding with Vector Data
Roger Ferrod, Maël Lecene, Krishna Sapkota +4
Precise spatial understanding in Earth Observation is essential for translating raw aerial imagery into actionable insights for critical applications like urban planning, environme…
cs.CV2026
IC-EO: Interpretable Code-based assistant for Earth Observation
Lamia Lahouel, Laurynas Lopata, Simon Gruening +3
Despite recent advances in computer vision, Earth Observation (EO) analysis remains difficult to perform for the laymen, requiring expert knowledge and technical capabilities. Furt…
cs.CV2025
Checkmate: interpretable and explainable RSVQA is the endgame
Lucrezia Tosato, Christel Tartini Chappuis, Syrielle Montariol +3
Remote Sensing Visual Question Answering (RSVQA) presents unique challenges in ensuring that model decisions are both understandable and grounded in visual content. Current models…