Brush

BrushSizzleCompressedFrame.mp4

Massive thanks to @GradeEterna for the beautiful scenes

Brush is a 3D reconstruction engine using Gaussian splatting. It works on a wide range of systems: macOS/windows/linux, AMD/Nvidia/Intel cards, Android, and in a browser. To achieve this, it uses WebGPU compatible tech and the Burn machine learning framework.

Machine learning for real time rendering has tons of potential, but most ML tools don't work well with it: Rendering requires realtime interactivity, usually involve dynamic shapes & computations, don't run on most platforms, and it can be cumbersome to ship apps with large CUDA deps. Brush on the other hand produces simple dependency free binaries, runs on nearly all devices, without any setup.

Try the web demo NOTE: Only works on Chrome 135+ as of June 2025. Firefox and Safari are hopefully supported soon

Features

Training

Brush takes in posed image data. It can load COLMAP data or datasets in the Nerfstudio format. Training is fully supported natively, on mobile, and in a browser.

While training you can interact with the scene and see the training dynamics live, and compare the current rendering to training or eval views as the training progresses.

It also supports masking images:

• Images with transparency. This will force the final splat to match the transparency of the input.
• A folder of images called 'masks'. This ignores parts of the image that are masked out.

Viewer

Brush also works well as a splat viewer, including on the web. It can load .ply & .compressed.ply files. You can stream in data from a URL (for a web app, simply append ?url=).

Brush also can load .zip of splat files to display them as an animation, or a special ply that includes delta frames (see cat-4D and Cap4D!).

CLI

Brush can be used as a CLI. Run brush --help to get an overview. Every CLI command can work with --with-viewer which also opens the UI, for easy debugging.

Rerun

rerun_dash_compressed.mp4

While training, additional data can be visualized with the excellent rerun. To install rerun on your machine, please follow their instructions. Open the ./brush_blueprint.rbl in the viewer for best results.

Building Brush

First install rust 1.85+. You can run tests with cargo test --all. Brush uses the wonderful rerun for additional visualizations while training, run cargo install rerun-cli if you want to use it.

Windows/macOS/Linux

Simply cargo run or cargo run --release from the workspace root. Brush can also be used as a CLI, run cargo run --release -- --help to use the CLI directly from source. See the notes about the CLI in the features section.

Web

This project uses trunk to build for the web. Install trunk, and then run trunk serve or trunk serve --release to run a development server.

WebGPU is still a new standard, and as such, only Chrome 134+ work currently.

Android

As a one time setup, make sure you have the Android SDK & NDK installed.

• Check if ANDROID_NDK_HOME and ANDROID_HOME are set
• Add the Android target to rust rustup target add aarch64-linux-android
• Install cargo-ndk to manage building a lib cargo install cargo-ndk

Each time you change the rust code, run

• cargo ndk -t arm64-v8a -o crates/brush-app/app/src/main/jniLibs/ build
• Nb: Nb, for best performance, build in release mode. This is separate from the Android Studio app build configuration.
• cargo ndk -t arm64-v8a -o crates/brush-app/app/src/main/jniLibs/ build --release

You can now either run the project from Android Studio (Android Studio does NOT build the rust code), or run it from the command line:

./gradlew build
./gradlew installDebug
adb shell am start -n com.splats.app/.MainActivity

You can also open this folder as a project in Android Studio and run things from there.

Nb: Running in Android Studio does not rebuild the rust code automatically.

Results

Metric	bicycle	garden	stump	room	counter	kitchen	bonsai	Average
PSNR ↑
inria 30K	25.25	27.41	26.55	30.63	28.70	30.32	31.98	28.69
gsplat 30K	25.22	27.32	26.53	31.36	29.02	31.16⭐	32.06⭐	28.95
brush 30K	25.55⭐	27.42⭐	26.88⭐	31.45⭐	29.17⭐	30.55	32.02	29.01⭐
SSIM ↑
inria 30k	0.763	0.863	0.771	0.918⭐	0.906	0.925	0.941	0.870
gsplat	0.764	0.865	0.768	0.918⭐	0.907	0.926⭐	0.941	0.870
brush	0.781⭐	0.869⭐	0.791⭐	0.916	0.909⭐	0.920	0.942⭐	0.875⭐
Splat Count (millions) ↓
inira	6.06	5.71	4.82	1.55	1.19	1.78	1.24	3.19
gsplat	6.26	5.84	4.81	1.59	1.21	1.79	1.25	3.25
brush	3.30⭐	2.90⭐	2.55⭐	0.75⭐	0.60⭐	0.79⭐	0.68⭐	1.65⭐
Minutes (4070 ti)
brush	35	35	28	18	19	18	18	24.43

Numbers taken from here. Note that Brush by default regularizes opacity slightly.

Benchmarks

Rendering is generally faster than gsplat, while end-to-end training speeds are similar. You can run benchmarks of some of the kernels using cargo bench.

Acknowledgements

gSplat, for their reference version of the kernels

Peter Hedman, George Kopanas & Bernhard Kerbl, for the many discussions & pointers.

The Burn team, for help & improvements to Burn along the way

Raph Levien, for the original version of the GPU radix sort.

GradeEterna, for feedback and displaying their scenes.

Disclaimer

This is not an official Google product. This repository is a forked public version of the google-research repository