3D Gaussian Splatting: Hands-on Course (Desktop Edition)
This is a session for 3D Gaussian Splatting, Hands-on. It highlights four main things:
the importance of filtering out noise in technology advancements, specifically in the rapidly evolving field of 3D Gaussian Splating.
the concepts like Structure from Motion, Gaussian Splat, and 3D Point Clouds, emphasizing their role in 3D modeling and rendering.
How to use Post-Shot software for 3D reconstruction, training Gaussian splats, adjusting parameters, and exporting point clouds for further analysis.
A discussion on sharing resources, joining the 3D community, and recommendations for Python libraries to compute Gaussian splats.
🍇 RESOURCES
All Material (.pdf, dataset, slides): https://learngeodata.eu/3d-gaussian-s...
3D Point Cloud Feature Extraction with Python:
Part 1: • 3D Point Cloud Feature Extraction Tutorial...
Part 2: • How to Build a 3D Interactive App in Pytho...
3D Tutorial Series: https://learngeodata.eu/3d-tutorials/
🙋 FOLLOW ME
Linkedin: / florent-poux-point-cloud
Medium: / florentpoux
Github: https://github.com/florentPoux
Research: https://scholar.google.com/citations?...
WHO AM I?
If we haven’t yet before - Hey 👋 I’m Florent, a professor-turned-entrepreneur, and I’ve somehow become one of the most-followed 3D expert. Through my videos here on this channel and my writing, I share evidence-based strategies and tools to help you be better coders and 3D innovators.
CHAPTERS 🌱
[00:00:00]: Introduction to 3D Gaussian Splating
[00:01:25]: Overview of Photogrammetry and Structure from Motion
[00:04:01]: Concepts of Gaussian Splating and Point Clouds
[00:06:31]: Back-end Solutions for Processing 3D Data
[00:07:52]: Rasterization and Stochastic Gradient Descent
[00:09:20]: Differentiable Gaussian Rasterizer and Loss Computation
[00:10:36]: Densification and Pruning of the Data Set
[00:13:18]: Setting Up Post-Shot Software and Data Import
[00:16:03]: Rendering and Exporting Point Clouds
[00:19:57]: Point Cloud Processing
[00:47:30]: Q&A 3D Gaussian Splatting
[00:55:18]: 3D Gaussian Splatting - Conclusion