3D Gaussian Splatting (3DGS) has significantly advanced 3D scene reconstruction and novel view synthesis. However, like Neural Radiance Fields (NeRF), 3DGS struggles with accurately modeling physical reflections, particularly in mirrors, leading to incorrect reconstructions and inconsistent reflective properties. To address this challenge, we introduce Mirror-3DGS, a novel framework designed to accurately handle mirror geometries and reflections, thereby generating realistic mirror reflections. By incorporating mirror attributes into 3DGS and leveraging plane mirror imaging principles, Mirror-3DGS simulates a mirrored viewpoint from behind the mirror, enhancing the realism of scene renderings. Extensive evaluations on both synthetic and real-world scenes demonstrate that our method can render novel views with improved fidelity in real-time, surpassing the state-of-the-art Mirror-NeRF, especially in mirror regions.
@article{arxiv.2404.01168,
title = {Mirror-3DGS: Incorporating Mirror Reflections into 3D Gaussian Splatting},
author = {Jiarui Meng and Haijie Li and Yanmin Wu and Qiankun Gao and Shuzhou Yang and Jian Zhang and Siwei Ma},
journal= {arXiv preprint arXiv:2404.01168},
year = {2024}
}
Comments
IEEE International Conference on Visual Communications and Image Processing (VCIP 2024, Oral)