7.2 KiB
| title |
|---|
| NeRF |
Intro
The field of 3D scanning encompasses a wide range of applications, NeRF makes a few of those applications a lot easier. The concept of using 3D scanning as an alternative means for people to interact with their surroundings is intriguing. For instance, museums could 3D scan their entire collections, or capture high-quality scans of monuments at risk of being lost forever. Additionally, education can be enhanced by introducing more active learning methods based on working in 3D. All of this is better served by how easy it is to produce models using a more software-defined method like NeRF.
Though techniques such as NeRF, MIP-NeRF, 3D Gaussians, and others demonstrate a fast and simpler method of 3D scanning compared to traditional laser or projection scanning. Neural network based scanning is still not considered a perfect "production ready" method, these models are made up of very dense point clouds that can not easily be translated into CAD. Supplimentary software is getting better but laser and projection scanning is still the best for high-accuracy work.
3D guassians have been a new focus of research, you can use an entirely software-defined approach to create very light (the below model is 6MB) and high quality 3D models. With polygon-based models you would have never been able to get this amount of accuracy in a 3D model that can run on a phone.
Showcase
3D Gaussian Splatting
Below you can see an example of a 3D guassian using the method "Splatfacto", created by the engineers working on the nerfstudio project inspired by the SIGGRAPH paper "3D Gaussian Splatting for Real-Time Rendering of Radiance Fields".
<head> </head>
left click rotate, right click pan
NeRF
Below are some pre-rendered photos based on the Nerfacto method also developed by nerfstudio. Though I have found that in some context the "splatting" method produces a smaller file and is more efficient to run, NeRF still provides pretty excellent quality.
{{< cards cols="2">}} {{< card title="Generated" subtitle="Nerfacto" link="4000-001.min.webp" image="4000-001.min.webp" >}} {{< card title="Generated" subtitle="Nerfacto" link="4000-002.min.webp" image="4000-002.min.webp" >}} {{< card title="Reference" subtitle="Sony A6400" link="4000-003.min.webp" image="4000-003.min.webp" >}} {{< card title="Reference" subtitle="Sony A6400" link="4000-004.min.webp" image="4000-004.min.webp" >}} {{< /cards >}}
How-To
{{< callout type="info" >}} Hey! This page is a work in progress. If you'd like to assist in the process of writing, take a look at the git repository {{< /callout >}}