8 papers
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…
UNIGEOCLIP: Unified Geospatial Contrastive Learning
Guillaume Astruc, Eduard Trulls, Jan Hosang +2
The growing availability of co-located geospatial data spanning aerial imagery, street-level views, elevation models, text, and geographic coordinates offers a unique opportunity f…
Environmental Footprint of GenAI Research: Insights from the Moshi Foundation Model
Marta López-Rauhut, Loic Landrieu, Mathieu Aubry +1
New multi-modal large language models (MLLMs) are continuously being trained and deployed, following rapid development cycles. This generative AI frenzy is driving steady increases…
Order Matters: 3D Shape Generation from Sequential VR Sketches
Yizi Chen, Sidi Wu, Tianyi Xiao +2
VR sketching lets users explore and iterate on ideas directly in 3D, offering a faster and more intuitive alternative to conventional CAD tools. However, existing sketch-to-shape m…
Segmenting France Across Four Centuries
Marta López-Rauhut, Hongyu Zhou, Mathieu Aubry +1
Historical maps offer an invaluable perspective into territory evolution across past centuries--long before satellite or remote sensing technologies existed. Deep learning methods…
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…