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December 9, 2024
The reconstruction of indoor scenes presents a challenge due to complex spatial structures and frequently occurring textureless areas. While 3D Gaussian Splatting (3DGS) has made progress in new view synthesis and accelerated processing, surface reconstruction remains a complex problem. A new method called 2DGS-Room leverages the advantages of 2D Gaussian Splatting (2DGS) to enable high-resolution reconstructions of indoor scenes.
2DGS-Room uses a seed-guided mechanism to control the distribution of 2D Gaussians. The density of the seed points is dynamically optimized through adaptive growth and pruning mechanisms. These seed points form a stable framework that preserves the structure of the scene and precisely guides the distribution of the 2D Gaussians. This achieves an efficient and detailed representation of the indoor geometry.
To further improve geometric accuracy, 2DGS-Room integrates monocular depth and normal priors. The depth priors provide important information for detailed areas, while the normal priors support the reconstruction, particularly in textureless regions. By combining these priors, the method's robustness to different scene characteristics is increased, and the reconstruction quality is improved.
In addition to the priors, 2DGS-Room uses multi-view consistency conditions. Both geometric and photometric consistency are considered to minimize artifacts and further enhance the reconstruction quality. Considering multiple perspectives allows for a more comprehensive capture of the scene and leads to a more coherent and realistic representation of the interior space.
Extensive experiments on the ScanNet and ScanNet++ datasets show that 2DGS-Room achieves state-of-the-art results in indoor scene reconstruction. The method demonstrates its performance across various evaluation criteria and offers a promising solution for creating high-resolution 3D models of indoor spaces. The improved geometric accuracy and efficient processing make 2DGS-Room a valuable tool for applications in areas such as virtual reality, architecture, and interior design.
The development of 2DGS-Room underscores the importance of innovative approaches in 3D reconstruction. For companies like Mindverse, which develop AI-powered content tools, such advancements offer new opportunities. Integrating technologies like 2DGS-Room into the Mindverse platform could significantly simplify and accelerate the creation of realistic and detailed 3D content for various applications. From generating virtual environments to creating digital twins for architecture and design, the possibilities are numerous.
Bibliographie Zhang, W., Xiang, H., Liao, Z., Lai, X., Li, X., & Zeng, L. (2024). 2DGS-Room: Seed-Guided 2D Gaussian Splatting with Geometric Constrains for High-Fidelity Indoor Scene Reconstruction. arXiv preprint arXiv:2412.03428. Zhang, W. (2024). 2DGS-Room. https://valentina-zhang.github.io/2DGS-Room/ Bytez. (2024). 2DGS-Room: Seed-Guided 2D Gaussian Splatting with Geometric Constrains for High-Fidelity Indoor Scene Reconstruction. https://bytez.com/docs/arxiv/2412.03428/paper Lee-JaeWon. (2024). 2024-Arxiv-Paper-List-Gaussian-Splatting. https://github.com/Lee-JaeWon/2024-Arxiv-Paper-List-Gaussian-Splatting Zhao, Z. (2024, December 5). 2DGS-Room: Seed-Guided 2D Gaussian Splatting with Geometric Constrains for High-Fidelity Indoor Scene Reconstruction [Tweet]. Twitter. https://twitter.com/zhenjun_zhao/status/1864540207539700210 Lee-JaeWon. (2024). README.md. https://github.com/Lee-JaeWon/2024-Arxiv-Paper-List-Gaussian-Splatting/blob/main/README.md arXiv Sanity Lite. (2024). 2DGS-Room: Seed-Guided 2D Gaussian Splatting with Geometric Constrains for High-Fidelity Indoor Scene Reconstruction. https://arxiv-sanity-lite.com/?rank=pid&pid=2412.02075 Hedman, P., & Malmberg, F. (2024). SurfSplatting: Seamless Surface Reconstruction and View Synthesis from RGB-D Images. arXiv preprint arXiv:2403.01299. https://surfsplatting.github.io/assets/paper/paper.pdf Chaitanya, K. V. A., Kowligi, A., Iyer, S., & Chaudhuri, S. (2024). 2D Gaussian Splatting for Geometrically Accurate Radiance Fields. arXiv preprint arXiv:2406.03850. https://www.researchgate.net/publication/382238481_2D_Gaussian_Splatting_for_Geometrically_Accurate_Radiance_Fields