Spatial AI Notes & Deep Dives

3D Deep Learning

3D Deep Learning Complete Guide

The complete 101 on 3D deep learning in Python: why point clouds break ordinary networks, permutation invariance, honest data prep, and the road from PointNet to KPConv.

05 Aug 2026 Prof. Florent Poux

3D Computer Vision

3D Point Cloud Segmentation Complete Guide

A complete, practical 101 on 3D point cloud segmentation in Python: what it is, the method families, real Open3D code for RANSAC and DBSCAN, and the parameters that decide your results.

29 Jul 2026 Prof. Florent Poux

3D Reconstruction & Photogrammetry

3D Reconstruction Complete Guide

A folder of phone photos already holds a 3D model. This complete guide walks 3D reconstruction in Python end to end, from parallax and photogrammetry through AI depth to Gaussian splatting, with the real cost of each spelled out plainly.

22 Jul 2026 Prof. Florent Poux

LiDAR & Remote Sensing

LiDAR and Point Cloud Processing Complete Guide

The complete 101 guide to LiDAR point cloud processing in Python. Read LAS files with laspy, index with an Open3D KDTree, filter ground with CSF, build a DTM.

15 Jul 2026 Prof. Florent Poux

3D Python & Getting Started

3D Spatial AI The Complete Guide

Your 3D bookmarks are a pile of tutorials that never reference each other. Here is the whole field of 3D spatial AI with Python, six skills wired into one pipeline you can build.

08 Jul 2026 Prof. Florent Poux

3D Visualization & Web

Point Cloud Level of Detail in Python: Octrees, Frustum Culling, and Out-of-Core Rendering

A cloud bigger than your memory still spins at sixty frames a second. The trick is the one your maps app already plays on you: a pyramid of pre-cut tiles, called an octree, that loads detail only where you are looking. Here is the full machinery, with a runnable Python demo.

01 Jul 2026 Prof. Florent Poux