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Differentiable gaussian rasterization with depth, alpha, normal map and extra per-Gaussian attributes, also support camera pose gradient

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slothfulxtx/diff-gaussian-rasterization

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Differential Gaussian Rasterization

What's new : Except for the RGB image, we also support render depth map, alpha map, normal map and extra per-Gaussian attributes (both forward and backward process) compared with the original repository.

📣 We recently support computing the gradient w.r.t. camera pose. However, this feature hasn't been fully validated, thus we don't merge it into the main branch. You can switch to pose branch for more information. If you find any bugs, leave a message in the issues. Thank you!

We modify the dependency name as diff_gauss to avoid dependecy conflict with the original version. You can install our repo by executing the following command lines

git clone --recurse-submodules https://github.com/slothfulxtx/diff-gaussian-rasterization.git 
cd diff-gaussian-rasterization
python setup.py install

Here's an example of our modified differential gaussian rasterization repo

from diff_gauss import GaussianRasterizationSettings, GaussianRasterizer

rendered_image, rendered_depth, rendered_norm, rendered_alpha, radii, extra = rasterizer(
    means3D = means3D,
    means2D = means2D,
    shs = shs,
    colors_precomp = colors_precomp,
    opacities = opacity,
    scales = scales,
    rotations = rotations,
    cov3Ds_precomp = cov3D_precomp,
    extra_attrs = extra_attrs
)

Details:

  • Depth: By default, the depth is calculated as 'median depth', where the depth values of each pixels covered by 3D Gaussian Splatting are set to be the depth of the 3D Gaussian center. Thus, there exist numerical errors when the scales of 3D Gaussian are large. However, thanks to the densificaiton scheme, most 3D Gaussians are small. Currently, we ignore the numerical error of depth maps.
  • Normal: By default, the normal is considered as the shortest axis direction of the covariance matrix. Notably both the directions inwards and outwards the surface satisfy the above condition. To obtain a meaningful normal, we reverse the inwards directions using the view direction.
  • Per-Gaussian attributes: The maximum value of per-Gaussian attributes is 34, which is a magic number for my NVIDIA 3090 Ti GPU (larger value will raise error). If your compiling process raises error, you can change it to a lower value in cuda_rasterizer/auxiliary.h.

Used as the rasterization engine for the paper "3D Gaussian Splatting for Real-Time Rendering of Radiance Fields". If you can make use of it in your own research, please be so kind to cite us.

BibTeX

@Article{kerbl3Dgaussians,
      author       = {Kerbl, Bernhard and Kopanas, Georgios and Leimk{\"u}hler, Thomas and Drettakis, George},
      title        = {3D Gaussian Splatting for Real-Time Radiance Field Rendering},
      journal      = {ACM Transactions on Graphics},
      number       = {4},
      volume       = {42},
      month        = {July},
      year         = {2023},
      url          = {https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/}
}

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Differentiable gaussian rasterization with depth, alpha, normal map and extra per-Gaussian attributes, also support camera pose gradient

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