diff --git a/docs/nerfology/methods/splat.md b/docs/nerfology/methods/splat.md index 62ffae0a2..69303f357 100644 --- a/docs/nerfology/methods/splat.md +++ b/docs/nerfology/methods/splat.md @@ -31,6 +31,16 @@ Because the method trains on *full images* instead of bundles of rays, there is ### Running the Method To run splatfacto, run `ns-train splatfacto --data `. Just like NeRF methods, the splat can be interactively viewed in the web-viewer, loaded from a checkpoint, rendered, and exported. +We provide a few additional variants: + +| Method | Description | Memory | Speed | +| ---------------- | ------------------------------ | ------ | ------- | +| `splatfacto` | Default Model | ~6GB | Fast | +| `splatfacto-big` | More Gaussians, Higher Quality | ~12GB | Slower | + + +A full evalaution of Nerfstudio's implementation of Gaussian Splatting against the original Inria method can be found [here](https://docs.gsplat.studio/tests/eval.html). + #### Quality and Regularization The default settings provided maintain a balance between speed, quality, and splat file size, but if you care more about quality than training speed or size, you can decrease the alpha cull threshold (threshold to delete translucent gaussians) and disable culling after 15k steps like so: `ns-train splatfacto --pipeline.model.cull_alpha_thresh=0.005 --pipeline.model.continue_cull_post_densification=False --data `