Nicolas Longépé — accepted AI-conference papers

2025

TerraMind: Large-Scale Generative Multimodality for Earth Observation

Johannes Jakubik, Felix Yang, Benedikt Blumenstiel, Erik Scheurer, Rocco Sedona, Stefano Maurogiovanni +10

ICCV 2025poster

We present TerraMind, the first any-to-any generative, multi-modal foundation model for Earth observation (EO). Unlike other multimodal models, TerraMind is pretrained on dual-scale representations combining both token-level and pixel-level data across modalities. On a token level, TerraMind encodes…

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2024

Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting

Brandon Victor, Mathilde Letard, Peter Jack Naylor, Karim Douch, Nicolas Longépé, Zhen He +1

NeurIPS 2024poster

Floods are among the most common and devastating natural hazards, imposing immense costs on our society and economy due to their disastrous consequences. Recent progress in weather prediction and spaceborne flood mapping demonstrated the feasibility of anticipating extreme events and reliably detect…

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2021

DENETHOR: The DynamicEarthNET dataset for Harmonized, inter-Operable, analysis-Ready, daily crop monitoring from space

Lukas Kondmann, Aysim Toker, Marc Rußwurm, Andrés Camero, Devis Peressuti, Grega Milcinski +6

NeurIPS 2021poster

Recent advances in remote sensing products allow near-real time monitoring of the Earth’s surface. Despite increasing availability of near-daily time-series of satellite imagery, there has been little exploration of deep learning methods to utilize the unprecedented temporal density of observations.…

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