activity
20232026
most citedFoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring

5 citations · 14 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2026

Understanding Representation Gaps Across Scales in Tropical Tree Species Classification from Drone Imagery

Sulagna Saha, Arthur Ouaknine, Etienne Laliberté +7

Accurate classification of tropical tree species from unoccupied aerial vehicle (UAV) imagery remains challenging due to high species diversity and strong visual similarity among s…

cs.CV2026

Estimating Individual Tree Height and Species from UAV Imagery

Jannik Endres, Etienne Laliberté, David Rolnick +1

Accurate estimation of forest biomass, a major carbon sink, relies heavily on tree-level traits such as height and species. Unoccupied Aerial Vehicles (UAVs) capturing high-resolut…

cs.CV2026

SelvaMask: Segmenting Trees in Tropical Forests and Beyond

Simon-Olivier Duguay, Hugo Baudchon, Etienne Laliberté +3

Tropical forests harbor most of the planet's tree biodiversity and are critical to global ecological balance. Canopy trees in particular play a disproportionate role in carbon stor…

cs.CV2025

GreenHyperSpectra: A multi-source hyperspectral dataset for global vegetation trait prediction

Eya Cherif, Arthur Ouaknine, Luke A. Brown +7

Plant traits such as leaf carbon content and leaf mass are essential variables in the study of biodiversity and climate change. However, conventional field sampling cannot feasibly…

cs.CV2025★ 2 cited

SelvaBox: A high-resolution dataset for tropical tree crown detection

Hugo Baudchon, Arthur Ouaknine, Martin Weiss +5

Detecting individual tree crowns in tropical forests is essential to study these complex and crucial ecosystems impacted by human interventions and climate change. However, tropica…

cs.CV2025

Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery

Mélisande Teng, Arthur Ouaknine, Etienne Laliberté +3

Information on trees at the individual level is crucial for monitoring forest ecosystems and planning forest management. Current monitoring methods involve ground measurements, req…

cs.CV2025

Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery

Mélisande Teng, Arthur Ouaknine, Etienne Laliberté +3

The potential of tree planting as a natural climate solution is often undermined by inadequate monitoring of tree planting projects. Current monitoring methods involve measuring tr…

cs.CV2024★ 3 cited

Tree semantic segmentation from aerial image time series

Venkatesh Ramesh, Arthur Ouaknine, David Rolnick

Earth's forests play an important role in the fight against climate change, and are in turn negatively affected by it. Effective monitoring of different tree species is essential t…

cs.CV2023★ 5 cited

FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring

Nikolaos Ioannis Bountos, Arthur Ouaknine, Ioannis Papoutsis +1

Forests are vital to ecosystems, supporting biodiversity and essential services, but are rapidly changing due to land use and climate change. Understanding and mitigating negative…

cs.CV2023★ 4 cited

OpenForest: A data catalogue for machine learning in forest monitoring

Arthur Ouaknine, Teja Kattenborn, Etienne Laliberté +1

Forests play a crucial role in Earth's system processes and provide a suite of social and economic ecosystem services, but are significantly impacted by human activities, leading t…

physics.ao-ph2023

Detangling the role of climate in vegetation productivity with an explainable convolutional neural network

Ricardo Barros Lourenço, Michael J. Smith, Sylvia Smullin +3

Forests of the Earth are a vital carbon sink while providing an essential habitat for biodiversity. Vegetation productivity (VP) is a critical indicator of carbon uptake in the atm…