Label a 3D point cloud with any word you type. This complete guide walks the open-vocabulary 3D segmentation stack in Python: pretrained SAM cuts the scene, CLIP scores each region, and a scene graph lets an LLM answer questions about the space.
Open-Vocabulary 3D Segmentation Complete Guide Read More »
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.
Open-Vocabulary 3D Semantics in Python: SAM, CLIP, and DINOv2 (No Training) Read More »
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.
3D Spatial AI for AEC: The Offline Stack That Replaces 6 Weeks of BIM Work Read More »
By Dr. Florent Poux, PhD in 3D geospatial sciences | Author, 3D Data Science with Python (O’Reilly) | Published 30 June 2025 A 3D scene graph encodes what a point cloud cannot: how objects relate to each other, that a lamp sits on a table or a bookshelf stands against a wall. Building one in […]
3D Scene Graphs for Spatial AI with NetworkX and OpenUSD Read More »
