GauStudio: A Modular Framework for 3D Gaussian Splatting and Beyond

Autor:	Ye, Chongjie, Nie, Yinyu, Chang, Jiahao, Chen, Yuantao, Zhi, Yihao, Han, Xiaoguang
Rok vydání:	2024
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	We present GauStudio, a novel modular framework for modeling 3D Gaussian Splatting (3DGS) to provide standardized, plug-and-play components for users to easily customize and implement a 3DGS pipeline. Supported by our framework, we propose a hybrid Gaussian representation with foreground and skyball background models. Experiments demonstrate this representation reduces artifacts in unbounded outdoor scenes and improves novel view synthesis. Finally, we propose Gaussian Splatting Surface Reconstruction (GauS), a novel render-then-fuse approach for high-fidelity mesh reconstruction from 3DGS inputs without fine-tuning. Overall, our GauStudio framework, hybrid representation, and GauS approach enhance 3DGS modeling and rendering capabilities, enabling higher-quality novel view synthesis and surface reconstruction. Comment: Code: https://github.com/GAP-LAB-CUHK-SZ/gaustudio
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2403.19632 Zobrazit plný text záznamu View this record from Arxiv