Update documentation for 3DGS (nerfstudio-project#2780)

Adding 3rd party viewers for splats and other edits to gs documentation.

docs/extensions/blender_addon.md

@@ -6,7 +6,7 @@
 
 ## Overview
 
-This Blender add-on allows for compositing with a Nerfstudio render as a background layer by generating a camera path JSON file from the Blender camera path, as well as a way to import Nerfstudio JSON files as a Blender camera baked with the Nerfstudio camera path. This add-on also allows compositing multiple NeRF objects into a NeRF scene. This is achieved by importing a mesh or point-cloud representation of the NeRF scene from Nerfstudio into Blender and getting the camera coordinates relative to the transformations of the NeRF representation. Dynamic FOV from the Blender camera is supported and will match the Nerfstudio render. Perspective, equirectangular, VR180, and omnidirectional stereo (VR 360) cameras are supported. This add-on also supports Gaussian Splatting scenes as well, however equirectangular and VR video rendering is not currently supported.
+This Blender add-on allows for compositing with a Nerfstudio render as a background layer by generating a camera path JSON file from the Blender camera path, as well as a way to import Nerfstudio JSON files as a Blender camera baked with the Nerfstudio camera path. This add-on also allows compositing multiple NeRF objects into a NeRF scene. This is achieved by importing a mesh or point-cloud representation of the NeRF scene from Nerfstudio into Blender and getting the camera coordinates relative to the transformations of the NeRF representation. Dynamic FOV from the Blender camera is supported and will match the Nerfstudio render. Perspective, equirectangular, VR180, and omnidirectional stereo (VR 360) cameras are supported. This add-on also supports Gaussian Splatting scenes as well, however equirectangular and VR video rendering is not currently supported for splats.
 
 <center>
  <img width="800" alt="image" src="https://user-images.githubusercontent.com/9502341/211442247-99d1ebc7-3ef9-46f7-9bcc-0e18553f19b7.PNG">
@@ -109,6 +109,7 @@ This Blender add-on allows for compositing with a Nerfstudio render as a backgro
     <img width="300" alt="image" src="https://github-production-user-asset-6210df.s3.amazonaws.com/9502341/253217833-fd607601-2b81-48ab-ac5d-e55514a588da.png">
     </center>
 - Fisheye and orthographic cameras are not supported.
+- Renders with Gaussian Splats are supported, but the point cloud or mesh representation would need to be generated from training a NeRF on the same dataset.
 - A walkthrough of this section is included in the tutorial video.
 
 ## Create Blender Camera from Nerfstudio JSON Camera Path

docs/nerfology/methods/splat.md

@@ -1,29 +1,33 @@
 # Gaussian Splatting
-[3D Gaussian Splatting](https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/) was proposed in SIGGRAPH 2023 from INRIA, and is a completely 
-different method of representing radiance fields by explicitly storing a collection of 3D volumetric gaussians. These can be "splatted", or projected, onto a 2D image
-provided a camera pose, and rasterized to obtain per-pixel colors. Because rasterization is very fast on GPUs, this method can render much faster than neural representations
-of radiance fields.
+[3D Gaussian Splatting](https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/) was proposed in SIGGRAPH 2023 from INRIA, and is a completely different method of representing radiance fields by explicitly storing a collection of 3D volumetric gaussians. These can be "splatted", or projected, onto a 2D image provided a camera pose, and rasterized to obtain per-pixel colors. Because rasterization is very fast on GPUs, this method can render much faster than neural representations of radiance fields.
 
 ### Installation
-Nerfstudio uses [gsplat](https://github.com/nerfstudio-project/gsplat) as its gaussian rasterization backend, an in-house re-implementation which is meant to be more developer friendly. This can be installed with `pip install gsplat`. The associated CUDA code will be compiled the first time gaussian splatting is executed. Some users with PyTorch 2.0 have experienced issues with this, which can be resolved by either installing gsplat from source, or upgrading torch to 2.1.
+Nerfstudio uses [gsplat](https://github.com/nerfstudio-project/gsplat) as its gaussian rasterization backend, an in-house re-implementation which is designed to be more developer friendly. This can be installed with `pip install gsplat`. The associated CUDA code will be compiled the first time gaussian splatting is executed. Some users with PyTorch 2.0 have experienced issues with this, which can be resolved by either installing gsplat from source, or upgrading torch to 2.1.
 
 ### Data
-Gaussian Splatting works much better if you initialize it from pre-existing geometry, such as SfM points rom COLMAP. COLMAP datasets or datasets from `ns-process-data` will automatically save these points and initialize gaussians on them. Other datasets currently do not support initialization, and will initialize gaussians randomly. Initializing from other data inputs (i.e. depth from phone app scanners) may be supported in the future.
+Gaussian Splatting works much better if you initialize it from pre-existing geometry, such as SfM points from COLMAP. COLMAP datasets or datasets from `ns-process-data` will automatically save these points and initialize gaussians on them. Other datasets currently do not support initialization, and will initialize gaussians randomly. Initializing from other data inputs (i.e. depth from phone app scanners) may be supported in the future.
 
 Because gaussian splatting trains on *full images* instead of bundles of rays, there is a new datamanager in `full_images_datamanager.py` which undistorts input images, caches them, and provides single images at each train step.
 
 
 ### Running the Method
-To run gaussian splatting, run `ns-train gaussian-splatting --data <data>`. Just like NeRF methods, the splat can be interactively viewed in the web-viewer, rendered, and exported.
+To run gaussian splatting, run `ns-train gaussian-splatting --data <data>`. Just like NeRF methods, the splat can be interactively viewed in the web-viewer, loaded from a checkpoint, rendered, and exported.
 
 ### Details
 For more details on the method, see the [original paper](https://arxiv.org/abs/2308.04079). Additionally, for a detailed derivation of the gradients used in the gsplat library, see [here](https://arxiv.org/abs/2312.02121).
 
 ### Exporting splats
-Gaussian splats can be exported as a `.ply` file which are ingestable by a variety of online web viewers. You can do this via the viewer, or `ns-export gaussian-splat`. Currently splats can only be exported from trained splats, not from nerfacto.
+Gaussian splats can be exported as a `.ply` file which are ingestable by a variety of online web viewers. You can do this via the viewer, or `ns-export gaussian-splat --load-config <config> --output-dir exports/splat`. Currently splats can only be exported from trained splats, not from nerfacto.
+
+Nerfstudio gaussian splat exports currently supports multiple third-party splat viewers:
+- [Polycam Viewer](https://poly.cam/tools/gaussian-splatting)
+- [Playcanvas SuperSplat](https://playcanvas.com/super-splat)
+- [WebGL Viewer by antimatter15](https://antimatter15.com/splat/) 
+- [Spline](https://spline.design/) 
+- [Three.js Viewer by mkkellogg](https://github.com/mkkellogg/GaussianSplats3D)
 
 ### FAQ
 - Can I export a mesh or pointcloud?
-Currently these export options are not supported, but may in the future and contributions are always welcome!
+Currently these export options are not supported, but may become in the future. Contributions are always welcome!
 - Can I render fisheye, equirectangular, orthographic images?
 Currently, no. Gaussian splatting assumes a perspective camera for its rasterization pipeline. Implementing other camera models is of interest but not currently planned.