Short Summary
This transcript elaborates on the advancements in 3D rendering techniques, specifically comparing Neural Radiance Fields (NeRF) with a new method known as Gaussian Splatting.
The observation highlights how Gaussian Splatting allows for real-time rendering by utilizing Gaussian functions to represent scenes, which significantly enhances rendering speed and quality.
Key characteristics of both methods are discussed, including their capabilities and limitations, as well as insights into their applications and the underlying technology.
Key Points
- Rendering Speed: Gaussian Splatting allows near-instantaneous rendering, achieving up to 100 FPS, whereas NeRF typically renders much slower (e.g., 0.2 FPS).
- Neural Network Representation: NeRF represents scenes as a neural network trained on multi-camera data, while Gaussian Splatting represents scenes as a collection of points using Gaussian functions.
- Rasterization vs. Ray Tracing: Gaussian Splatting uses rasterization for quick rendering, unlike NeRF which relies on ray tracing leading to longer render times.
- Adaptability of Gaussian Splatting: Gaussians can adjust in size and number to accurately fit a scene, improving the model’s representation over time with optimization algorithms.
- Real-Time Adjustments: Gaussians can be manipulated easily in tools like Unity, unlike NeRF where adjustments require retraining the entire model.
- Visualization of Data: The transcript visualizes how Gaussian functions can create three-dimensional objects and their potential applications in gaming and simulations.
- Limitations: Both methods require sufficient data capture for effective rendering; areas not captured will render empty or black.
- Future Integrations: Potential for advancements, such as using diffusion models to fill in missing data or improve results even further.
This structured HTML document summarizes the provided content and highlights key points discussed in the transcript.
Youtube Channel: Computerphile
Video Published: 2024-03-14T15:45:11+00:00
Video Description:
A new technique to turn pictures of a scene into a 3D model is quick, easy and doesn’t require that much compute power! Dr Mike Pound and PhD student Lewis Stuart demo and explain.
Lewis used this Particle simulation in Unity: GitHub – keijiro/SplatVFX: https://github.com/keijiro/SplatVFX
NeRFStudio is here : https://docs.nerf.studio/index.html
,
Previous (nerf) video: https://youtu.be/wKsoGiENBHU
https://www.facebook.com/computerphile
Tweets by computer_phile
This video was filmed and edited by Sean Riley.
Computer Science at the University of Nottingham: https://bit.ly/nottscomputer
Computerphile is a sister project to Brady Haran’s Numberphile. More at https://www.bradyharanblog.com
Thank you to Jane Street for their support of this channel. Learn more: https://www.janestreet.com