Spatial AI Notes & Deep Dives

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

Point Cloud Processing

Open-Vocabulary 3D Semantics in Python: SAM, CLIP, and DINOv2 (No Training)

Turn a careless phone video into a labeled, scaled, measurable 3D room with pretrained SAM, CLIP, and DINOv2, and not one training run. A nine-step open-vocabulary 3D semantics pipeline in Python.

26 Jun 2026 Prof. Florent Poux

Scan-to-BIM & Digital Twins

3D Spatial AI for AEC: The Offline Stack That Replaces 6 Weeks of BIM Work

From the NXT BLD 2026 stage and the reality capture panel: the local-first cognition stack for 3D spatial AI for AEC. Smart point cloud in, IFC and decisions out, in three days, not six weeks.

19 May 2026 Prof. Florent Poux

3D Computer Vision

3D Point Cloud Labeling from Photos with Python (and why AI can’t design it for you)

A complete Python pipeline for 3D point cloud labeling from phone photos using interactive painting, pinhole projection, and KD-tree fusion — no GPU required.

03 Apr 2026 Prof. Florent Poux