3D Gaussian Splatting
3D Gaussian Splatting is a method for 3D scene reconstruction that represents scenes as millions of colored Gaussian ellipsoids and renders them in real-time.
3D Gaussian Splatting reconstructs photorealistic 3D scenes from photos and renders in real-time – faster and more editable than NeRF, ideal for product visualization.
Explanation
Instead of implicit neural representation (NeRF), 3DGS uses explicit point primitives. Advantages: real-time rendering, faster training, editable. From a few photos, an interactive 3D scene is created.
Marketing Relevance
Next level of product visualization: interactive 3D product views from smartphone photos for e-commerce, virtual try-on, VR/AR.
Example
An e-commerce team photographs a product from 20 angles – Gaussian Splatting creates an interactive 3D view for the website in minutes.
Common Pitfalls
High memory requirements (millions of Gaussians). Reflections/transparency still difficult. Web integration complex.
Origin & History
Kerbl et al. (INRIA/MPI, 2023) published "3D Gaussian Splatting for Real-Time Radiance Field Rendering" – immediately a paradigm shift in 3D reconstruction. Compared to NeRF: 100x faster rendering, 10x faster training. 2024 saw variants for dynamic scenes, generative 3DGS, and web viewers.
Comparisons & Differences
3D Gaussian Splatting vs. NeRF
NeRF uses implicit neural representation (slow but compact); 3DGS uses explicit Gaussians (fast but memory-intensive).
3D Gaussian Splatting vs. Photogrammetrie
3DGS creates point-based representations; photogrammetry creates traditional mesh geometry.