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LitePT: Lighter Yet Stronger Point Transformer
Yuanwen Yue, Damien Robert, Jianyuan Wang +4
Modern neural architectures for 3D point cloud processing contain both convolutional layers and attention blocks, but the best way to assemble them remains unclear. We analyse the…
EZ-SP: Fast and Lightweight Superpoint-Based 3D Segmentation
Louis Geist, Loic Landrieu, Damien Robert
Superpoint-based pipelines provide an efficient alternative to point- or voxel-based 3D semantic segmentation, but are often bottlenecked by their CPU-bound partition step. We prop…
Climplicit: Climatic Implicit Embeddings for Global Ecological Tasks
Johannes Dollinger, Damien Robert, Elena Plekhanova +2
Deep learning on climatic data holds potential for macroecological applications. However, its adoption remains limited among scientists outside the deep learning community due to s…
FORMSpoT: A Decade of Tree-Level, Country-Scale Forest Monitoring
Martin Schwartz, Fajwel Fogel, Nikola Besic +9
The recent decline of the European forest carbon sink highlights the need for spatially explicit and frequently updated forest monitoring tools. Yet, existing satellite-based distu…
SSL4Eco: A Global Seasonal Dataset for Geospatial Foundation Models in Ecology
Elena Plekhanova, Damien Robert, Johannes Dollinger +4
With the exacerbation of the biodiversity and climate crises, macroecological pursuits such as global biodiversity mapping become more urgent. Remote sensing offers a wealth of Ear…
GSR4B: Biomass Map Super-Resolution with Sentinel-1/2 Guidance
Kaan Karaman, Yuchang Jiang, Damien Robert +3
Accurate Above-Ground Biomass (AGB) mapping at both large scale and high spatio-temporal resolution is essential for applications ranging from climate modeling to biodiversity asse…