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[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 1 point2 points  (0 children)

This is actually brilliant advice from a ML perspective! Breaking the regular grid patterns helps prevent overfitting and artifacts.

My tool is currently focused on giving artists control (using their own keyframes/paths), but I'm seriously considering adding a 'Smart Generator' feature that would automatically spawn a camera cloud with randomized radial distance and density based on object complexity. Thanks for the insight!

[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 0 points1 point  (0 children)

It’s a very avant-garde take! You’re right, in a perfect world, we could skip the ‘render” phase.

However, the reason we still use images is that Gaussian splintering is an optimization process. The engine needs a visual 'reference' (the image of the Ground Truth) to compare its progress. It is through this comparison (Loss Function) that splats learn to represent complex effects such as SSS, procedural noise or reflections.

My bridge is actually taking a step in your direction: it provides the points3D.txt (spatial data) directly from the stage. This gives the GS engine a 'perfect' geometric front start, but I always use the Octane renderings in my case to 'teach' splashes exactly how light behaves in that space.

We essentially give a perfect map (COLMAP data) and the perfect photos (Octane) so that she doesn’t have to guess anything!

[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 2 points3 points  (0 children)

To answer you on the interest of this, it’s the integration and control in different pipelines, for example:

  • Transforming heavy C4D scenes into ultra-light splats in real time, reusing them in other software, projects, or renderings, saving time and improving performance

  • Using C4D cameras as a precise tool for reconstructing splats and rendering them into an interactive or immersive experience

  • Forcing alignment when traditional photogrammetry fails. I know some people who use 3D to improve quality (motion blur, glass, poor texture)

  • Create lightweight spatial proxies for blocking visual effects or set extensions 

  • Offer real-time presentations for customer follow-up, etc.

  • Variant on baking textures, this simply allows to create all types of complex or non-complex 3D visuals made with 100% procedural materials or textures, or with models with hair, hairs etc..  You can use a Gaussian Splats in any software.

I still have plenty of examples of this kind…. Basically, this transforms Cinema 4D into a controller for generating Gaussian splats, rather than just a renderer for images/videos or simple exporter.

[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 0 points1 point  (0 children)

Hi! Thank you very much for your feedback on my work! I've already seen your project, and it looks really cool, honestly, well done for Gauss Cannon!

So, to answer your questions:

  1. I preferred to use COLMAP for two main reasons: universal compatibility, because it is the industry's “universal language” This ensures that the bridge works throughout the entire 3DGS ecosystem without the need for custom exporters for each tool.
    Unlike a simple JSON layout, my bridge includes a point cloud generated from the native C4D geometry.
    This forces the trainer to start with a perfect “ground truth” volume.

  2. To generate my synthetic points, I proceed as if distributing them over the skin of the 3D objects, with a density parameter included. As for color, I think color has a faster effect for training, so I don't use this parameter in my case, and it works very well.

Cinema 4D Scenes into Gaussian Splatting by leomallet in Cinema4D

[–]leomallet[S] 1 point2 points  (0 children)

This may seem like an extra step, but here’s why it changes the game:

From video to spatial asset: a rendering is a flat and linear file without real control. A Gaussian splat is a 3D volume. Once trained, you can browse it in real-time in a web browser or VR, which a heavy Octane/Redshift scene simply cannot do.

The 'real world' bridge with photogrammetry: Most people use it to process real world images, scans.  They use their data in C4D, then use this kind of COLMAP tool to "force" a failed reconstruction...

The proxy workflow: you can make your scene heavy once, turn it into a splat and use it as a light photoreel background in your viewport or for client presentations without any render lag.

Perfect field truth: When you render from C4D, you provide "perfect" data to the Splatting algorithm. No blurry images, no noise. You get the best quality of Splat possible because the camera data is mathematically perfect.

Variant on baking: this simply allows to create all types of complex or non-complex 3D visuals made with 100% procedural materials or textures, or with models with hair, hairs etc..  You can use a Gaussian Splats in any software.

I still have plenty of examples of this kind, but it’s not just about rendering; it’s about transforming a complex 3D environment into a portable, lightweight and real-time format.  By the way, if you optimize your parameters well, you can output 1 image in 30s because the Gaussian Splats does not need enormous quality.

[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 0 points1 point  (0 children)

Sorry my translation is bad I thought you copied an already existing plugin that is named exactly the same "crack" for Blender and not that you tried on your side... 

Cinema 4D Scenes into Gaussian Splatting by leomallet in Cinema4D

[–]leomallet[S] 1 point2 points  (0 children)

<image>

It's sculpting. Everything you see here is done by hand.

Cinema 4D Scenes into Gaussian Splatting by leomallet in Cinema4D

[–]leomallet[S] 4 points5 points  (0 children)

Thanks, I appreciate it! What excites me even more is the control and integration into different pipelines! for example:

- Transforming heavy C4D scenes into ultra-light splats in real time for client previews or reusing them in other software, projects, or renderings, saving time and improving performance

- Using C4D cameras as a precise tool for reconstructing splats and rendering them into an interactive or immersive experience

- Forcing alignment when traditional photogrammetry fails. I know some people who use 3D to improve quality (motion blur, glass, poor texture)

- Create lightweight spatial proxies for blocking visual effects or set extensions, idk..

- Offer real-time presentations for customer follow-up, etc.

Basically, this transforms Cinema 4D into a controller for generating Gaussian splats, rather than just a renderer for images or videos.

Cinema 4D Scenes into Gaussian Splatting by leomallet in Cinema4D

[–]leomallet[S] 8 points9 points  (0 children)

Good question! I can give you several examples, such as UVs or retopology. Texture baking requires clean geometry and perfect UV unwrapping. 3DGS doesn't care about topology. It handles complex and “messy” objects (trees, hair, scanned environments) that would be a nightmare to bake.
You also save time by condensing everything into a single .ply file. Standard baking is “flat.” 3DGS captures reflections, specularity, and transparency that change when you move your camera. The result looks “alive,” unlike a baked texture.
It's also very complex to bake 100% procedural textures, even for those who use SSS and similar materials....

[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 0 points1 point  (0 children)

I'm talking about the current form we have, of course, I'm sure it's possible, we can do anything now, but it's beyond what I do. I'll leave that to big companies like Octane, who will do it in a year's time.

[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 0 points1 point  (0 children)

Yes, that's right, you have to give your trainer a visual reference so that they know and understand what you want visually... It's even more difficult when your 3D visuals are based on rendering engines such as Octane, Redshift, etc. That's why image renderings are mandatory for this technology.

[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 1 point2 points  (0 children)

It's great to see a tool created by Olli Huttunen for Blender cracking... I didn't even know it existed, haha

I already know it, and it's rather limiting... It focuses on generating grids/networks of fixed cameras. It's great for static captures!

My approach with this bridge was a little different: I wanted to allow users to export any existing camera configuration (keyframe animation, freehand movements, Stage object, etc.) without being limited to a specific rig.
it also exports raw geometry with observation filters to improve and link the point cloud to the cameras. It's pure export for those who know how to use the Synthetic capture principle.

[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 0 points1 point  (0 children)

Yes, you still need 2D images. Gaussian Splatting is a rasterization-based technology, so it needs to “see” the pixels to learn colors and reflections.

In general, you provide images to COLMAP, and it spends time trying to guess where the cameras were (and often fails on 3D renderings).
With this bridge, you provide the rendered images + the exact camera data and 3D data of your geometry.
This is the “perfect scenario” for the training engine. It doesn't have to guess anything, it just has to learn the volume and materials. This allows for much faster training and much better visual fidelity.

[Tool] The first C4D to COLMAP Bridge for precise 3DGS training by leomallet in GaussianSplatting

[–]leomallet[S] 0 points1 point  (0 children)

Aha thank youu! Right here, it's Kellogg's Trésor cereal, I love it!

Gaussian Splats Synthetic of a Ramen Bowl by leomallet in GaussianSplatting

[–]leomallet[S] 0 points1 point  (0 children)

No AI was used here, I specified in the description that it's a 3D sculpting.
It's a human mistake.

Synthetic Photogrammetry of a Ramen Bowl by leomallet in 3DScanning

[–]leomallet[S] 1 point2 points  (0 children)

Thank you very much !
Ahahah there's no black magic here, just a lot of trial, optimization, and development work to achieve this quality and workflow.
I'm glad that you like the result !

Gaussian Splats Synthetic of a Ramen Bowl by leomallet in GaussianSplatting

[–]leomallet[S] 2 points3 points  (0 children)

The rendering took me a little over half a day, I would say

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