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transparentgs

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[SIGGRAPH'25 (ACM TOG)] TransparentGS: Fast Inverse Rendering of Transparent Objects with Gaussians

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<h1 align="center">TransparentGS: Fast Inverse Rendering of Transparent Objects with Gaussians</h1>
<h3 align="center">SIGGRAPH 2025 (ACM Transactions on Graphics)</h3>

<a href="https://letianhuang.github.io/">Letian Huang</a>1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 <a href="https://orcid.org/0009-0004-8637-4384">Dongwei
 Ye</a>1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 <a href="https://orcid.org/0009-0007-2228-4648">Jialin Dan</a>1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 <a href="https://orcid.org/0000-0002-0736-7951">Chengzhi
 Tao</a>1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 <a href="https://orcid.org/0009-0005-6423-4812">Huiwen Liu</a>2&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 
 <a href="http://kunzhou.net/">Kun Zhou</a>3,4&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 <a href="http://ren-bo.net/">Bo Ren</a>2&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 <a href="http://www.njumeta.com/liyq/">Yuanqi Li</a>1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 <a href="https://cs.nju.edu.cn/ywguo/index.htm">Yanwen Guo</a>1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 <a href="https://scholar.google.com.hk/citations?user=Sx4PQpQAAAAJ&hl=en">Jie Guo</a>*
 1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 1State Key Lab for Novel Software Technology, Nanjing
 University 
 2TMCC, College of Computer Science, Nankai University 
 3State Key Lab of CAD&CG, Zhejiang University 
 4Institute of Hangzhou Holographic Intelligent Technology

![teaser](https://github.com/LetianHuang/LetianHuang.github.io/blob/main/assets/img/transparent_teaser.png)

## News

**[2025.08.04]** 🎈 We release the code.

**[2025.07.23]** <img class="emoji" title=":smile:" alt=":smile:" src="https://github.githubassets.com/images/icons/emoji/unicode/1f604.png" height="20" width="20"> Birthday of the repository.

## TL;DR

We propose TransparentGS, a fast inverse rendering pipeline for transparent objects based on 3D-GS. The main contributions are three-fold: efficient transparent Gaussian primitives for specular refraction, GaussProbe to encode ambient light and nearby contents, and the IterQuery algorithm to reduce parallax errors in our probe-based framework.

## Overview

The overview of our TransparentGS pipeline. Each 3D scene is firstly separated into transparent objects and opaque environment using SAM2 [Ravi et al. 2024] guided by GroundingDINO [Liu et al. 2024]. For transparent objects, we propose transparent Gaussian primitives, which explicitly encode both geometric and material properties within 3D Gaussians. And the properties are rasterized into maps for subsequent deferred shading. For the opaque environment, we recover it with the original 3D-GS, and bake it into GaussProbe surrounding the transparent object. The GaussProbe are then queried through our IterQuery algorithm to compute reflection and refraction.

![pipeline](https://letianhuang.github.io/transparentgs/static/images/exp/pipeline.png)

## Citation

If you find this work useful in your research, please cite:

```bibtex
@article{transparentgs,
    author = {Huang, Letian and Ye, Dongwei and Dan, Jialin and Tao, Chengzhi and Liu, Huiwen and Zhou, Kun and Ren, Bo and Li, Yuanqi and Guo, Yanwen and Guo, Jie},
    title = {TransparentGS: Fast Inverse Rendering of Transparent Objects with Gaussians},
    journal = {ACM Transactions on Graphics (TOG)},
    number = {4},
    volume = {44},
    month = {July},
    year = {2025},
    pages = {1--17},
    url = {https://doi.org/10.1145/3730892},
    publisher = {ACM New York, NY, USA}
}
```

## TODO List

- [x] Release the [rendering code](#transparentgs-viewer-renderer).
- [x] Release the [dataset](#dataset) of transparent objects that we captured ourselves.
- [x] Support the shadow mapping.
- [x] Release the code of [segmentation code](#standalone-demo--segmentation).
- [x] Release the [training/reconstruction code](#training-pipeline).

## TransparentGS Viewer (Renderer)

### Functions

- [x] Real-time rendering and navigation of scenes that integrate traditional [3DGS](https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/), triangle meshes and reconstructed meshes (Highly robust to complex occlusions).
- [x] Secondary light effects (e.g., reflection and refraction).
- [x] Rendering with non-pinhole camera models (e.g., fisheye or panorama).
- [x] Material editing (e.g., IOR and base color).
- [x] Compatible with [2DGS](https://surfsplatting.github.io/) and supporting scene-level $360^{\circ}$ shadow mapping (shown as follows).

![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/garden_2DGS_relighting_shadow_transparent.gif)

![TransparentGS Renderer](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/TransparentGS_viewer_utility.png)

### Software Requirements

Because this repository is built upon 3DGS, it is recommended to follow [3DGS](https://github.com/graphdeco-inria/gaussian-splatting)'s software requirements (as follows); otherwise, the setup/build may fail (e.g., issue [#3](https://github.com/LetianHuang/transparentgs/issues/3)).

* Conda (recommended for easy setup)
* C++ Compiler for PyTorch extensions (we used Visual Studio 2019 for Windows)
* CUDA SDK 11 for PyTorch extensions, install after Visual Studio (we used 11.8, known issues with 11.6)
* C++ Compiler and CUDA SDK must be compatible

### Cloning the Repository and Setup

Clone the repository and create an anaconda environment using

``` shell
git clone git@github.com:LetianHuang/transparentgs.git --recursive
cd transparentgs

SET DISTUTILS_USE_SDK=1 # Windows only
conda env create --file environment.yml
conda activate transparentgs
```

<details>
<summary>About the Eigen C++ library</summary>

It is notable that the Eigen C++ library `eigen==3.4.0` should be downloaded with `https://gitlab.com/libeigen/eigen/-/archive/3.4.0/eigen-3.4.0.zip` and put into the specified path shown in `setup.py`:
  ``` shell
  /usr/include/eigen3
  /usr/local/include/eigen3 
  # or
  C:/Program Files/eigen3
  C:/Program Files (x86)/eigen3
  ```
If, for some reason, it doesn't work, you can try downloading it from this [Google Drive link](https://drive.google.com/drive/folders/19KTRAkcYs1NOBhnzng6ScNwere9Qsbvv?usp=sharing).

</details>

The repository contains several submodules, thus please check it out with

``` shell
pip install . # Thanks to https://github.com/ashawkey/raytracing
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn
pip install submodules/diff-gaussian-rasterization-fisheye 
pip install submodules/diff-gaussian-rasterization-panorama
pip install submodules/diff-surfel-rasterization # Newly Added
pip install submodules/diff-gaussian-rasterization_light # Newly Added
pip install submodules/nvdiffrast
```

or choose a faster version (1. integrated with [Speedy-Splat](https://github.com/j-alex-hanson/speedy-splat), using SnugBox and AccuTile; 2. Employ CUDA scripting for computational acceleration of 64 probes).

``` shell
pip install . 
pip install submodules-speedy/diff-gaussian-rasterization
pip install submodules/simple-knn
pip install submodules-speedy/diff-gaussian-rasterization-fisheye
pip install submodules-speedy/diff-gaussian-rasterization-panorama
pip install submodules/diff-surfel-rasterization  # fast version (TODO)
pip install submodules/diff-gaussian-rasterization_light # fast version (TODO)
pip install submodules-speedy/compute-trilinear-weights
pip install submodules/nvdiffrast
```

### Scene Assets

First, create a `models` folder inside the project path by

```shell
mkdir models
```

The data structure will be organised as follows:

```
transparentgs/
│── models/
│   ├── 3dgs/
│   │   ├── drjohnson.ply
│   │   ├── playroom_lego_hotdog_mouse.ply
│   │   ├── Matterport3D_h1zeeAwLh9Z_3.ply
│   │   ├── ...
│   ├── 2dgs/ (Newly Added)
│   │   ├── garden.ply
│   │   ├── ...
│   ├── mesh/
│   │   ├── ball.ply
│   │   ├── mouse.ply
│   │   ├── bunny.ply
│   │   ├── ...
│   ├── probes/
│   │   ├── playroom_lego_hotdog_mouse/
│   │   │   ├── probes/
│   │   │   │   ├── 000_depth.exr
│   │   │   │   ├── 000.exr
│   │   │   │   ├── 333_depth.exr
│   │   │   │   ├── 333.exr
│   │   │   │   ├── ...
│   │   │   ├── probe.json
│   │   ├── ...
|   ├── meshgs_proxy/
│   │   ├── mouse.ply
│   │   ├── ...
```

#### Public scene

We release several ready-to-use scenes. Please download the assets from [Google Drive](https://drive.google.com/drive/folders/1SS7E74DapiaBWNOMLp-n0FP1hqjX42cK?usp=sharing) and move the `3dgs` (or `2dgs`, Newly Added) and `mesh` folders into `models/` folder.

#### Custom scene

To create a custom scene, simply follow the provided instructions to set it up. Instructions on the above data structure are as follows:

1. Scenes in the `3dgs` folder should be in `.ply` format and reconstructed using traditional [3DGS](https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/), [op43dgs](https://github.com/LetianHuang/op43dgs) (for reconstruction from non-pinhole cameras) or [Mip-Splatting](https://niujinshuchong.github.io/mip-splatting/) (for anti-alias).
2. Objects in the `mesh` folder could be in any triangle mesh format (e.g, `.obj`, `.ply` or `.glb`), including both traditional and reconstructed ones.
3. Probes in the `probes` folder could be baked using `Step I: Bake GaussProbe` or similar formats. The `probes.json` file specifies the positions of the probes, while the `probes/` directory stores the corresponding RGB panorama and depth panorama in EXR format.
4. The `meshgs_proxy` folder is a byproduct of `Step I: Bake GaussProbe`. It contains the object converted into 3DGS format and can be used as a proxy of the mesh in `mesh` to assemble a new scene (`mesh` + `3DGS`). Note: modifying the files in `meshgs_proxy` does not affect the final rendering results (i.e., `Step II: Boot up the renderer`). To change the proxy configuration, you can adjust the scene’s position under the 3dgs directory and rerun `Step I: Bake GaussProbe`.
5. (Newly Added) Scenes in the `2dgs` folder should be in `.ply` format and reconstructed using [2DGS](https://surfsplatting.github.io/).

### Step I: Bake GaussProbe

The first step is to bake probes for the scene that has already been set up:

``` shell
python probes_bake.py --W 800 --H 800 --gs_path ./models/3dgs/playroom_lego_hotdog_mouse.ply --probes_path ./models/probes/playroom_lego_hotdog_mouse --mesh ./models/mesh/mouse.ply --begin_id 0
```

<details>
<summary>Command Line Arguments for probes_bake.py</summary>

#### --gs_path 
  path to the trained 3D Gaussians directory as the environment (used to bake GaussProbe).
  #### --probes_path
  output path of GaussProbe to be baked
  #### --mesh
  path to the mesh
  #### --W
  width of the RGBD panorama
  #### --H
  height of the RGBD panorama
  #### --numProbes
  number of probes (1/8/64). In theory, any positive integer is allowed, but the released code only supports these three fixed values.
  #### --begin_id
  only to prevent OOM (Out of Memory); when GPU memory is insufficient, the process can exit and resume baking from the specified ID.
  #### --scale_ratio
  bounding box scale ratio for the mesh
  #### --meshproxy_pitch
  the voxel size (pitch), which determines the resolution of the mesh voxelization.

</details>

### Step II: Boot up the renderer

Next, boot the renderer to start rendering:

``` shell
python renderer.py --W 960 --H 540 --gs_path ./models/3dgs/playroom_lego_hotdog_mouse.ply --probes_path ./models/probes/playroom_lego_hotdog_mouse --mesh ./models/mesh/mouse.ply --meshproxy_pitch 0.1
```

<details>
<summary>Command Line Arguments for renderer.py</summary>

#### --mesh
  path to the mesh
  #### --light_type
  the original design supports either environment map or GaussProbe. However, since a single probe with zero iteration is equivalent to the environment map, this design has been deprecated.
  #### --gs_path 
  path to the trained 3D Gaussians directory as the environment (used to bake GaussProbe).
  #### --W
  GUI width
  #### --H
  GUI height
  #### --radius
  default GUI camera radius from center
  #### --fovy
  default GUI camera fovy (can be modified in the GUI)
  #### --probes_path
  path of the baked GaussProbe
  #### --numProbes
  number of probes (1/8/64). In theory, any positive integer is allowed, but the released code only supports these three fixed values. (can be modified in the GUI)
  #### --iters
  count of iterations (0-10). In theory, any non-negative integer is allowed, but the released code only supports these eleven fixed values. (can be modified in the GUI)
  #### --meshproxy_pitch
  the voxel size (pitch), which determines the resolution of the mesh voxelization.

</details>

### Full Pipeline (optional)

Additionally, we offer an optional all-in-one pipeline script that produces the same effect as executing `Step I` and `Step II` independently:

``` shell
python full_render_pipeline.py --W 960 --H 540 --probesW 800 --probesH 800 --gs_path ./models/3dgs/playroom_lego_hotdog_mouse.ply --probes_path ./models/probes/playroom_lego_hotdog_mouse --mesh ./models/mesh/mouse.ply --meshproxy_pitch 0.1
# equal to
# 1. python probes_bake.py --W 800 --H 800 --gs_path ./models/3dgs/playroom_lego_hotdog_mouse.ply --probes_path ./models/probes/playroom_lego_hotdog_mouse --mesh ./models/mesh/mouse.ply --begin_id 0 --meshproxy_pitch 0.1
# 2. python renderer.py --W 960 --H 540 --gs_path ./models/3dgs/playroom_lego_hotdog_mouse.ply --probes_path ./models/probes/playroom_lego_hotdog_mouse --mesh ./models/mesh/mouse.ply --meshproxy_pitch 0.1
```

or for [2DGS](https://surfsplatting.github.io/) (Newly Added):

```shell
python full_render_pipeline.py --W 960 --H 540 --probesW 800 --probesH 800 --gs_path ./models/2dgs/garden.ply --probes_path ./models/probes/garden_ball --mesh ./models/mesh/ball.ply --meshproxy_pitch 0.1 --numProbes 64
# equal to
# 1. python probes_bake.py --W 800 --H 800 --gs_path ./models/2dgs/garden.ply --probes_path ./models/probes/garden_ball --mesh ./models/mesh/ball.ply --begin_id 0 --numProbes 64
# 2. python renderer.py --W 960 --H 540 --gs_path ./models/2dgs/garden.ply --probes_path ./models/probes/garden_ball --mesh ./models/mesh/ball.ply --meshproxy_pitch 0.1 --numProbes 64
```

<details>
<summary>Command Line Arguments for renderer.py</summary>

</details>

### Renderer GUI Tutorial

The following GUI usage tutorial is provided based on the current release. It is recommended to watch this in conjunction with the video available on the [project homepage](https://letianhuang.github.io/transparentgs/).

![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial.png)

#### Move the camera

Bear resemblance to [raytracing](https://github.com/ashawkey/raytracing/).

1. **drag rotate:** move with the left mouse button.
  2. **drag translation:** move with the middle mouse button
  3. **move closer:** move with the wheel

#### Options and Debug

1. **Options**: the main ways to control, aside from moving the camera.
  2. **Debug**: display the camera pose.

#### gbuffers in Options

Common G-buffers in typical renderers (`depth`, `mask`, `normal`, `position`), with special attention to:

1. **reflect**: the reflection component (mesh).
  ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_reflect.png)
  also works for 2DGS
  ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_2dgs_reflect.png)
  2. **refract**: the refraction component (mesh).
  ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_refract.png)
  3. **render**: the weighted sum of the reflection and refraction components using the Fresnel term (mesh).
  ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_render.png)
  also works for 2DGS
  ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_2dgs_refract.png)
  4. **gs_render**: the rendering result obtained using only traditional Gaussian primitives (3DGS).
  ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_gs_render.png)
  5. **semantic**: the result of hybrid rendering with Gaussians and meshes (mesh + 3DGS). Pixels belonging to the mesh are replaced with a uniform color that represents the same semantic label (e.g., purple).
   ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_semantic.png)
  6. **2dgs_render**: (Newly Added, only work for `2dgs`) the rendering result obtained using 2DGS.
   ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_2dgs_render.png)
  7. **2dgs_normal**: (Newly Added, only work for `2dgs`) the normal map obtained using 2DGS.
   ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_2dgs_normal.png)
  8. **2dgs_depth**: (Newly Added, only work for `2dgs`) the depth map obtained using 2DGS.
   ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_2dgs_depth.png)
  9. **2dgs_relighting**: (Newly Added, only work for `2dgs`) the relighting result with shadow obtained using 2DGS.
   ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_gbuffers_2dgs_relighting.png)

#### camera

Select the camera model.

1. **pinhole**: the regular camera model which 3DGS also supports.
 2. **fisheye**: It can support a field of view (FOV) of up to 180°.
  ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_camera_fisheye.png)
 3. **panorama**: It can support a field of view (FOV) of 360°.
 ![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_camera_panorama.png)

#### bkg

Select the background of the mesh.

1. **black**: black color as the background
  2. **white**: white color as the background
  3. **3DGS**: Hybrid rendering of 3DGS and transparent objects (`reflect`, `refract`, `render`, `normal`).

#### normal mode

Select whether to apply normal smoothing.

1. **raw**: no
![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_normal_raw.png)
2. **smooth**: yes
![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_normal_smooth.png)

#### num probes

As changing the number of probes involves I/O overhead, it is not recommended to modify it through the GUI. It is advisable to configure it beforehand using terminal arguments. Additionally, increasing the number of probes demands more GPU memory.

#### num iters

Modify the count of iterations of IterQuery (0-10). In theory, any non-negative integer is allowed, but the released code only supports these eleven fixed values. Setting it to zero clearly demonstrates the superiority of the IterQuery.

#### FoV (y)

Modifying the field of view (FOV), particularly for `fisheye` cameras, allows reaching up to a 180° viewing angle.

#### IOR

![Alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/GUI_tutorial_ior_gsscale.png)

This mainly affects gbuffers with `refract` or `render` properties. When the IOR is approximately 1, the result is almost identical to the background, demonstrating the high quality of IterQuery (especially with 64 probes).

#### GS scale

Note that only the scale of the `3dgs` primitives is modified, not the overall scene scaling. Therefore, reducing the scale allows us to observe the gaps between Gaussians.

#### spp

Control the sampling rate of mesh ray tracing.

#### Pick a color

Modify the color of the mesh.

## Dataset

We release several self-captured scenes for reconstruction purposes. Please download the transparent object dataset from [Google Drive](https://drive.google.com/drive/folders/1J8H6VCA1tOKnzLXXOEopzAAZY9OOlWO3?usp=sharing).

## Standalone demo : Segmentation

Please refer to [grounded_sam2](https://github.com/LetianHuang/transparentgs/blob/main/grounded_sam2/README.md).

## Training Pipeline

The environtment of this part is the same as the [renderer/viewer](#transparentgs-viewer-renderer).

Assume that you have already segmented the scene using the [segmentation](#standalone-demo--segmentation) module we have released, and that you have reconstructed the opaque environment with the original [3D Gaussian Splatting](https://github.com/graphdeco-inria/gaussian-splatting), resulting in the `mask` directory and `env_gs.ply`, respectively. In other words, you should have obtained a dataset with a structure similar to the [dataset](#dataset) we have released.

A simple example is as follows:

``` shell
python simple_full_recon_pipeline.py \
    -s {DATA_PATH} \
    -m {MODEL_PATH} \
    --probesW {resolution of probes} \
    --probesH {resolution of probes} \
    --numProbes 64 \
    --meshproxy_pitch 0.1 \
    --scale_ratio {scale ratio of aabb} \
    --skip_base {skip baking if you have baked} \
    --viewer {use this argument if you wanna see the rendering result} \
    --viewer_mode {view the coarse or fine version} \
    --sdf_end_iter {iterations for the SDF} \
    --mesh_end_iter {iterations for the mesh proxy part} \
    --mesh_r {image resolution for the mesh proxy part} \
    ... # the same as the original 3DGS
```

More details and explanations on this part will be released soon, subject to our available time. In addition, we would like to sincerely thank our collaborators for taking the time out of their busy schedules to help organize this part.

![alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/Training_demo1.png)
![alt text](https://raw.githubusercontent.com/LetianHuang/transparentgs/main/assets/Training_demo2.png)

## Acknowledgements

This project is built upon [3DGS](https://github.com/graphdeco-inria/gaussian-splatting), [GaussianShader](https://github.com/Asparagus15/GaussianShader), [GlossyGS](https://letianhuang.github.io/glossygs/), [op43dgs](https://github.com/LetianHuang/op43dgs), [raytracing](https://github.com/ashawkey/raytracing), [nvdiffrast](https://github.com/NVlabs/nvdiffrast), [instant-ngp](https://github.com/NVlabs/instant-ngp), [SAM2](https://github.com/facebookresearch/sam2), [GroundingDINO](https://github.com/IDEA-Research/GroundingDINO), [SAM](https://github.com/facebookresearch/segment-anything), [GroundedSAM](https://github.com/IDEA-Research/Grounded-Segment-Anything), [2DGS](https://github.com/hbb1/2d-gaussian-splatting), [GS$^{3}$](https://github.com/gsrelight/gs-relight), [NeuS](https://github.com/Totoro97/NeuS), [NeTO](https://github.com/xxlong0/NeTO) and so on. Please follow the licenses. We thank all the authors for their great work and repos. We sincerely thank our colleagues for their valuable contributions to this project.

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