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20222026
most citedLossy Neural Compression for Geospatial Analytics: A Review

5 citations · 13 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.CV2025

FORMSpoT: Revealing Fine-Scale Forest Disturbances from Nation-Wide 1.5 m Forest Canopy Height Time Series

Martin Schwartz, Fajwel Fogel, Nikola Besic +9

Current large-scale satellite-based forest disturbance monitoring systems operate at 10-30~m resolution, too coarse to detect changes at the scale of individual trees and resulting…

cs.CV2025★ 1 cited

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

eess.SP2025★ 5 cited

Lossy Neural Compression for Geospatial Analytics: A Review

Carlos Gomes, Isabelle Wittmann, Damien Robert +24

Over the past decades, there has been an explosion in the amount of available Earth Observation (EO) data. The unprecedented coverage of the Earth's surface and atmosphere by satel…