Stars
Implementations of popular CNNs in 3D for developing forest inventories from LiDAR
A Python package for creating interactive maps with anywidget and JavaScript mapping libraries
View & explore data from LVIS collected during the NASA Arctic Boreal Vulnerability Experiment (ABoVE).
A CloudCompare Python plugin for a suite of LiDAR processing modules targeting forest and tree analysis.
A collection of tools to calculate tree- or stand-level attributes developed for Canadian forests
OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generation [SIGGRAPH 2025]
A Pacific Northwest inspired R color palette package
DRI-EDIA Project: Advancing Equity in Forestry: Digital Research Infrastructure and Deep Learning for All
Project developed for a Kaggle Competition organised by CentraleSupelec Deep Learning course. Final result: 1st place
[NeurIPS 2023] PointGPT: Auto-regressively Generative Pre-training from Point Clouds
OctFormer: Octree-based Transformers for 3D Point Clouds [SIGGRAPH 2023]
Open vocabulary interactions with remote sensing images.
[ECCV2022] Masked Autoencoders for Point Cloud Self-supervised Learning
Additional point cloud metrics to use with *_metric functions in lidR
This is the repository for the 'Remote Sensing of Environment' article: Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR
[GCPR 2023 | CVPR 2023 Workshop] Self-Supervised Representation Learning on Point Clouds
interactive notebooks from Planet Engineering
Code and Tutorials for the 2023 Silvilaser GEDI Workshop
This repository provides the code used to create the results presented in "Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles".
An open-source benchmark framework for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO)
AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.