12 citations · 14 across the 7 of their papers we have counts for
9 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…
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…
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…
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…
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…
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…
OmniSat: Self-Supervised Modality Fusion for Earth Observation
Guillaume Astruc, Nicolas Gonthier, Clement Mallet +1
The diversity and complementarity of sensors available for Earth Observations (EO) calls for developing bespoke self-supervised multimodal learning approaches. However, current mul…
StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation
Sidi Wu, Yizi Chen, Samuel Mermet +4
Most image-to-image translation models postulate that a unique correspondence exists between the semantic classes of the source and target domains. However, this assumption does no…
FLAIR: a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery
Anatol Garioud, Nicolas Gonthier, Loic Landrieu +5
We introduce the French Land cover from Aerospace ImageRy (FLAIR), an extensive dataset from the French National Institute of Geographical and Forest Information (IGN) that provide…