MirrorGaussian: Reflecting 3D Gaussians for Reconstructing Mirror Reflections
CoRR(2024)
摘要
3D Gaussian Splatting showcases notable advancements in photo-realistic and
real-time novel view synthesis. However, it faces challenges in modeling mirror
reflections, which exhibit substantial appearance variations from different
viewpoints. To tackle this problem, we present MirrorGaussian, the first method
for mirror scene reconstruction with real-time rendering based on 3D Gaussian
Splatting. The key insight is grounded on the mirror symmetry between the
real-world space and the virtual mirror space. We introduce an intuitive
dual-rendering strategy that enables differentiable rasterization of both the
real-world 3D Gaussians and the mirrored counterpart obtained by reflecting the
former about the mirror plane. All 3D Gaussians are jointly optimized with the
mirror plane in an end-to-end framework. MirrorGaussian achieves high-quality
and real-time rendering in scenes with mirrors, empowering scene editing like
adding new mirrors and objects. Comprehensive experiments on multiple datasets
demonstrate that our approach significantly outperforms existing methods,
achieving state-of-the-art results. Project page:
https://mirror-gaussian.github.io/.
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