Florent Poux, Ph.D. – Medium

Florent Poux, Ph.D.

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Florent Poux, Ph.D.
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Towards Data Science

3D Python Workflows for LiDAR City Models: A Step-by-Step Guide

The Ultimate Guide to unlocking a streamlined workflow for 3D City Modelling Applications. The tutorial covers Python Automation combining…

38 min readApr 4, 2023

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3D Python Workflows for LiDAR City Models: A Step-by-Step Guide by Florent Poux

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Florent Poux, Ph.D.
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Towards Data Science

3D Machine Learning 201 Guide: Point Cloud Semantic Segmentation

Complete python tutorial to create supervised learning AI systems for semantic segmentation of unstructured 3D LiDAR point cloud data.

24 min readJun 29, 2022

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3D Machine Learning tutorial: How to develop a Semantic Segmentation Framework for 3D LiDAR Point Cloud Data by Florent Poux

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Florent Poux, Ph.D.
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Towards Data Science

Guide to real-time visualisation of massive 3D point clouds in Python

Tutorial for advanced visualization with big point cloud data in Python. (Bonus) Learn how to create an interactive segmentation “software”

13 min readFeb 15, 2021

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Guide to real-time visualisation of massive 3D point clouds in Python

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Florent Poux, Ph.D.
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Towards Data Science

How to Automate Voxel Modelling of 3D Point Cloud with Python

Hands-on tutorial to turn large point clouds into 3D voxels 🧊 with Python and open3d. Unlock an automation workflow for efficient 3D…

12 min readDec 13, 2021

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How to Automate Voxel Modelling of 3D Point Cloud with Python

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Florent Poux, Ph.D.

3D Deep Learning Roadmap to Future-Proof Your Career (+19 Resources)

How to leverage 3D Deep Learning to develop solutions beyond 2D pixels.

18 min readMar 13, 2024

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Roadmap to Learn 3D Deep Learning. Image by Florent Poux

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Florent Poux, Ph.D.
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Towards Data Science

The Blender Handbook for 3D Point Cloud Visualization and Rendering

Complete guide to create 3D experiences with large point clouds in Blender

20 min readFeb 28, 2024

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The Blender Handbook for 3D Point Cloud Visualization and Rendering

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Florent Poux, Ph.D.
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Towards Data Science

Segment Anything 3D for Point Clouds: Complete Guide (SAM 3D)

How to build a semantic segmentation application for 3D point clouds leveraging SAM and Python

27 min readDec 13, 2023

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The Segment Anything Model for 3D Environments. We will detect objects in indoor spaces using 3D point cloud datasets. Credit goes to Mimatelier, the talented illustrator who created this image.

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Florent Poux, Ph.D.
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Towards Data Science

3D Geospatial Data Integration with Python: The Ultimate Guide

Tutorial to integrate geospatial data with a multi-modal Python workflow: combine 3D point clouds, CityGML, voxels, vector + raster data

39 min readNov 7, 2023

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How to create Spatial Digital World through 3D Data Integration. Many sources of information, such as vector, raster data, 3D point clouds, or 3D city models, can be combined to form a unified view of what happens on our planet. © F. Poux

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Towards AI

Towards 3D Deep Learning: Artificial Neural Networks with Python

A Hands-on Beginner's Guide to Unlock the Power of Artificial Neural Networks in Python

11 min readSep 14, 2023

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Towards 3D Deep Learning: Artificial Neural Networks with Python

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Florent Poux, Ph.D.
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Towards Data Science

3D Point Cloud Shape Detection for Indoor Modelling

A 10-step Python Guide to Automate 3D Shape Detection, Segmentation, Clustering, and Voxelization for Space Occupancy 3D Modeling of Indoor…

28 min readSep 7, 2023

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3D Point Cloud Shape Detection for Indoor Modelling

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Florent Poux, Ph.D.

Florent Poux, Ph.D.

Code and Ideas for 3D Data Science & Research | Director of Innovation | Award-winning Senior Researcher & Engineer | Online course at: https://learngeodata.eu

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