BiGS: Bidirectional Gaussian Primitives for Relightable 3D Gaussian Splatting

Zhenyuan Liu, Yu Guo, Xinyuan Li, Bernd Bickel, Ran Zhang
8/23/2024
cs.CVcs.GR

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Abstract

We present Bidirectional Gaussian Primitives, an image-based novel view synthesis technique designed to represent and render 3D objects with surface and volumetric materials under dynamic illumination. Our approach integrates light intrinsic decomposition into the Gaussian splatting framework, enabling real-time relighting of 3D objects. To unify surface and volumetric material within a cohesive appearance model, we adopt a light- and view-dependent scattering representation via bidirectional spherical harmonics. Our model does not use a specific surface normal-related reflectance function, making it more compatible with volumetric representations like Gaussian splatting, where the normals are undefined. We demonstrate our method by reconstructing and rendering objects with complex materials. Using One-Light-At-a-Time (OLAT) data as input, we can reproduce photorealistic appearances under novel lighting conditions in real time.

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@article{liu2024bigs,
  title  = {BiGS: Bidirectional Gaussian Primitives for Relightable 3D Gaussian Splatting},
  author = {Zhenyuan Liu and Yu Guo and Xinyuan Li and Bernd Bickel and Ran Zhang},
  year   = {2024},
  eprint = {2408.13370},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2408.13370v1}
}

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