From 8952fb531ea09db00c481de95cafadbb80c262e6 Mon Sep 17 00:00:00 2001 From: "J.Y" <132313008+jb-ye@users.noreply.github.com> Date: Sat, 20 Jan 2024 00:15:00 -0500 Subject: [PATCH] important fix typo (#2800) fix typo Co-authored-by: Jianbo Ye --- docs/nerfology/methods/splat.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/nerfology/methods/splat.md b/docs/nerfology/methods/splat.md index f36973bd0..62ffae0a2 100644 --- a/docs/nerfology/methods/splat.md +++ b/docs/nerfology/methods/splat.md @@ -33,7 +33,7 @@ To run splatfacto, run `ns-train splatfacto --data `. Just like NeRF metho #### 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_scale_thresh=0.005 --pipeline.model.continue_cull_post_densification=False --data ` +(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 ` A common artifact in splatting is long, spikey gaussians. [PhysGaussian](https://xpandora.github.io/PhysGaussian/) proposes a scale regularizer that encourages gaussians to be more evenly shaped. To enable this, set the `use_scale_regularization` flag to `True`.