activity
20242026
collaborators

6 papers

cs.CV2026

Analytical Logit Scaling for High-Resolution Sea Ice Topology Retrieval from Weakly Labeled SAR Imagery

Reda Elwaradi, Julien Gimenez, Stéphane Hordoir +3

High-resolution sea ice mapping using Synthetic Aperture Radar (SAR) is crucial for Arctic navigation and climate monitoring. However, operational ice charts provide only coarse, r…

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…

cs.CV2025

SAR Strikes Back: A New Hope for RSVQA

Lucrezia Tosato, Flora Weissgerber, Laurent Wendling +1

Remote Sensing Visual Question Answering (RSVQA) is a task that extracts information from satellite images to answer questions in natural language, aiding image interpretation. Whi…

cs.CV2025

Visual Question Answering on Multiple Remote Sensing Image Modalities

Hichem Boussaid, Lucrezia Tosato, Flora Weissgerber +3

The extraction of visual features is an essential step in Visual Question Answering (VQA). Building a good visual representation of the analyzed scene is indeed one of the essentia…

cs.CV2024

Can SAR improve RSVQA performance?

Lucrezia Tosato, Sylvain Lobry, Flora Weissgerber +1

Remote sensing visual question answering (RSVQA) has been involved in several research in recent years, leading to an increase in new methods. RSVQA automatically extracts informat…

cs.CV2024

Segmentation-guided Attention for Visual Question Answering from Remote Sensing Images

Lucrezia Tosato, Hichem Boussaid, Flora Weissgerber +3

Visual Question Answering for Remote Sensing (RSVQA) is a task that aims at answering natural language questions about the content of a remote sensing image. The visual features ex…