collaborators

6 papers

cs.CV2026

UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation

Yohann Perron, Guillaume Astruc, Nicolas Gonthier +2

Vision Transformers (ViT) dominate computer vision. However, their reliance on rigid patch projectors hinders transfer to Earth Observation (EO), where input modalities, scales, an…

cs.CV2026

FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping

Anatol Garioud, Sébastien Giordano, Nicolas David +1

The growing availability of high-quality Earth Observation (EO) data enables accurate global land cover and crop type monitoring. However, the volume and heterogeneity of these dat…

cs.CV2025

Operational Change Detection for Geographical Information: Overview and Challenges

Nicolas Gonthier

Rapid evolution of territories due to climate change and human impact requires prompt and effective updates to geospatial databases maintained by the National Mapping Agency. This…

cs.CV2025

MAESTRO: Masked AutoEncoders for Multimodal, Multitemporal, and Multispectral Earth Observation Data

Antoine Labatie, Michael Vaccaro, Nina Lardiere +2

Self-supervised learning holds great promise for remote sensing, but standard self-supervised methods must be adapted to the unique characteristics of Earth observation data. We ta…

cs.CV2025

AnySat: One Earth Observation Model for Many Resolutions, Scales, and Modalities

Guillaume Astruc, Nicolas Gonthier, Clement Mallet +1

Geospatial models must adapt to the diversity of Earth observation data in terms of resolutions, scales, and modalities. However, existing approaches expect fixed input configurati…

cs.CV2025

The Change You Want To Detect: Semantic Change Detection In Earth Observation With Hybrid Data Generation

Yanis Benidir, Nicolas Gonthier, Clement Mallet

Bi-temporal change detection at scale based on Very High Resolution (VHR) images is crucial for Earth monitoring. This remains poorly addressed so far: methods either require large…