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20172026
most citedDeep learning in remote sensing: a review

3.2k citations · 5.7k across the 32 of their papers we have counts for

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45 papers · 1 filter

cs.CV2026

Knowledge-aware Visual Question Generation for Remote Sensing Images

Siran Li, Li Mi, Javiera Castillo-Navarro +1

With the rapid development of remote sensing image archives, asking questions about images has become an effective way of gathering specific information or performing image retriev…

cs.CV2026

Questions beyond Pixels: Integrating Commonsense Knowledge in Visual Question Generation for Remote Sensing

Siran Li, Li Mi, Javiera Castillo-Navarro +1

With the rapid development of remote sensing image archives, asking questions about images has become an effective way of gathering specific information or performing semantic imag…

cs.CV2025

An Efficient and Effective Encoder Model for Vision and Language Tasks in the Remote Sensing Domain

João Daniel Silva, Joao Magalhaes, Devis Tuia +1

The remote sensing community has recently seen the emergence of methods based on Large Vision and Language Models (LVLMs) that can address multiple tasks at the intersection of com…

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

TRUST: Leveraging Text Robustness for Unsupervised Domain Adaptation

Mattia Litrico, Mario Valerio Giuffrida, Sebastiano Battiato +1

Recent unsupervised domain adaptation (UDA) methods have shown great success in addressing classical domain shifts (e.g., synthetic-to-real), but they still suffer under complex sh…

cs.CV2025

GeoExplorer: Active Geo-localization with Curiosity-Driven Exploration

Li Mi, Manon Bechaz, Zeming Chen +2

Active Geo-localization (AGL) is the task of localizing a goal, represented in various modalities (e.g., aerial images, ground-level images, or text), within a predefined search ar…