8 papers
SpectralEarth-FM: Bringing Hyperspectral Imagery into Multimodal Earth Observation Pretraining
Nassim Ait Ali Braham, Aaron Banze, Conrad M. Albrecht +3
Earth observation (EO) foundation models (FMs) are increasingly trained on multisensor data, spanning multispectral imagery (MSI), synthetic aperture radar (SAR), and derived geosp…
Data-Centric Benchmark for Label Noise Estimation and Ranking in Remote Sensing Image Segmentation
Keiller Nogueira, Codrut-Andrei Diaconu, Dávid Kerekes +9
High-quality pixel-level annotations are essential for the semantic segmentation of remote sensing imagery. However, such labels are expensive to obtain and often affected by noise…
SSL4EO-S12 v1.1: A Multimodal, Multiseasonal Dataset for Pretraining, Updated
Benedikt Blumenstiel, Nassim Ait Ali Braham, Conrad M Albrecht +2
This work presents SSL4EO-S12 v1.1, a multimodal, multitemporal Earth Observation dataset designed for pretraining large-scale foundation models. Building on the success of SSL4EO-…
SpectralEarth: Training Hyperspectral Foundation Models at Scale
Nassim Ait Ali Braham, Conrad M Albrecht, Julien Mairal +3
Foundation models have triggered a paradigm shift in computer vision and are increasingly being adopted in remote sensing, particularly for multispectral imagery. Yet, their potent…
HyBiomass: Global Hyperspectral Imagery Benchmark Dataset for Evaluating Geospatial Foundation Models in Forest Aboveground Biomass Estimation
Aaron Banze, Timothée Stassin, Nassim Ait Ali Braham +3
Comprehensive evaluation of geospatial foundation models (Geo-FMs) requires benchmarking across diverse tasks, sensors, and geographic regions. However, most existing benchmark dat…
Hyperspectral Vision Transformers for Greenhouse Gas Estimations from Space
Ruben Gonzalez Avilés, Linus Scheibenreif, Nassim Ait Ali Braham +8
Hyperspectral imaging provides detailed spectral information and holds significant potential for monitoring of greenhouse gases (GHGs). However, its application is constrained by l…