collaborators

5 papers

cs.LG2026

STeMP: Spatio-Temporal Modelling Protocol

Jan Linnenbrink, Jakub Nowosad, Marvin Ludwig +4

Spatio-temporal machine-learning modelling is an important tool in environmental research. However, machine-learning models are highly sensitive to both the characteristics of the…

cs.CV2026

SelectAnyTree: A Promptable Instance Segmentation Model for 3D Forest LiDAR Point Clouds

Trung Thanh Nguyen, Daniel Lusk, Kilian Gerberding +10

Automated instance segmentation of forest LiDAR point clouds is increasingly critical as forest monitoring moves toward scalable, detailed, 3D measurement. Yet, progress is constra…

cs.CV2026

ForestMamba: Sparse Mamba with Geometry-guided Queries for 3D Forest Point Cloud Segmentation

Trung Thanh Nguyen, Tuan-Anh Vu, Duc Viet Le +4

Semantic and instance segmentation of terrestrial and drone LiDAR point clouds is emerging as a transformative approach for converting the complex 3D structure of forests into acti…

cs.CV2026

deadtrees.earth-aerial: A Multi-Resolution Aerial Image Dataset for Tree Cover and Mortality Detection

Ayushi Sharma, Clemens Mosig, Lukas Drees +9

Forests worldwide are increasingly threatened by climate change and disturbances such as fire, pests, and pathogens, creating an urgent need for scalable monitoring of tree cover a…

cs.CV2024

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…