Awesome 3D Knowledge (Production in 2024)

Resources authored by 🦊 Florent Poux to learn about 3D Data Science. You have two main sections:

• Premium (8%): This includes the most complete and refined pieces, either books or courses, with code (commercially usable).
• Open-Access (92%): This includes standalone pieces, with MIT or CC-NC licenses, to learn and create POCs.

The Premium helps me build the Open-Access. My aim for 2025 is a 1%-to-99% ratio. If you want to support 💖 this endeavour while learning: Get a 3D Book or join a 3D Course OS.

Christmas Specials 🎁

3D Datasets as an image (.png), a 3D Point Cloud (.ply) and a 3D Mesh (.glb) from a Image-to-3D GenAI Solution

• The purple Christmas Tree - Download the tree files (.png, .ply, .glb)
• The 3D Tech Reindeer - Download the reindeer files (.png, .ply, .glb)
• The Santa - Download the santa files (.png, .ply, .glb)

Premium 🌟

Books (x1)

3D Data Science with Python - O’Reilly, 650 pages, 2025

3D Courses (x3)

1. 3D Creator OS: 3D Reconstruction and Point Cloud Processing
2. 3D Segmentor OS: 3D Data Science and Algorithms
3. 3D Deep Learning: State-of-the-art AI Systems

Open-Access 🎓

Tutorial Articles (x7)

1. 3D Clustering with Graph Theory: The Complete Guide - 22 min read
2. Transform Point Clouds into 3D Meshes: A Python Guide - 15 min read
3. Learn to Visualize Massive Point Clouds + 3D Mesh with No-Code Tools - 11 min read
4. Ultimate Guide: 3D Data Science Systems and Tools - 17 min read
5. 3D Reconstruction Tutorial with Python and Meshroom - 5 min read
6. 3D Deep Learning Roadmap to Future-Proof Your Career (+19 Resources) - 18 min read
7. The Blender Handbook for 3D Point Cloud Visualization and Rendering - 20 min read

Video Tutorials (x35, 17.5 hours)

To better organize your learning journey, these are sorted based on their main topic

3D Gaussian Splatting

1. 3D Gaussian Splatting With Postshot (And Point Cloud Editing)
2. 3D Gaussian Splatting: My 9-Step Editing Workflow (For Point Cloud Retouching)
3. 3D Gaussian Splatting: Hands-On Course (Desktop Edition)

3D Modelling / GenAI

1. 2D Images To 3D Models: Quick Guide (End-To-End 3D Reconstruction)
2. 3D Python Tutorial: Building 3D Models From 2D Images (Photo Or AI) With 5 Libraries
3. Create Stunning 3D Mesh From Point Clouds (Python Version)
4. Create An App To Generate 3D Mesh From Point Clouds (Marching Cubes Tutorial)
5. Turn 2D Images To 3D Normals With Python + Dsine (Live Session)
6. 2D Image To 3D Point Cloud With Depthanything: Live Course (Monocular Depth Estimation)
7. My 11 Tools For 3D Generative AI
8. 3D Point Clouds In Blender: Starter Guide

3D Data Processing

1. 3D Point Cloud Processing (OS Edition)
2. 3D Point Cloud Workflow Fundamentals
3. 3D Point Cloud Processing Starter Pack
4. How To Generate 3D Voxels From Point Clouds With Python (Tutorial)
5. Innovative Guide To Massive (1b+) Point Cloud Instant Visualization (No-Code Approach)
6. How To Compute Pca And Visualize 3D Point Cloud With Python (Principal Component Analysis 3D Course)
7. 3D Point Cloud Feature Extraction Tutorial For Interactive Python App Development
8. How To Build A 3D Interactive App In Python: Point Cloud Feature Extraction Tutorial (Part 2)
9. Lidar Point Cloud Vectorization: 3D Python Tutorial (+ Lod City Models)
10. 3D Point Cloud Segmentation And Shape Recognition With Python

3D Python

1. How To Build 3D Data Tools In Python: The Ultimate Beginner's Guide
2. I Build 3D Apps With This Simple Python Stack (Beginner's Guide)
3. Python Programming Setup For 3D Data
4. Real-Time Visualization And Interactive Segmentation: 3D Python Tutorial
5. 3D Point Cloud Processing With Python: Live Workshop

3D Scene Understanding

1. How To Label 3D Point Cloud For AI Systems: Semi-Automated Workflow
2. Active Learning For 3D Data Labelling: 9-Step Workflow
3. 3D Clustering Mastery: How To Segment Point Clouds With Graph Theory
4. 3D Shape Detection With Ransac + Python On Point Clouds
5. 3D Semantic Segmentation With Kpconv: Live Course
6. 3D Point Cloud Segmentation With Superpoint Transformers (And Python)

Research Articles (x3)

1. Explainable Neural Subgraph Matching With Learnable Multi-Hop Attention - D. Q. Nguyen, T. Toan Nguyen, J. Jo, F. Poux, S. Anirban and T. T. Quan - IEEE Access - 2024
2. Investigating Deep Learning Techniques to Estimate Fractional Vegetation Cover in the Australian Semi-arid Ecosystems combining Drone-based RGB imagery, multispectral Imagery and LiDAR data. L Sotomayor, T Kattenborn, F Poux, D Turner… - 2024
3. Investigating Prior-Level Fusion Approaches for Enriched Semantic Segmentation of Urban LiDAR Point Clouds Z Ballouch, R Hajji, A Kharroubi, F Poux, R Billen - Remote Sensing, 2024

Career, Innovation, Research

1. My 2024 Roadmap For 3D Creators, Researchers, Coders And Innovators (In 7 Steps)
2. 3D Deep Learning Workflows And Challenges
3. 3D Deep Learning Demystified: Your Roadmap To Building 3D AI Apps