GT2-GS: Geometry-aware Texture Transfer for Gaussian Splatting
Wenjie Liu, Zhongliang Liu, Junwei Shu, Changbo Wang, Yang Li
Abstract
Transferring 2D textures onto complex 3D scenes plays a vital role in enhancing the efficiency and controllability of 3D multimedia content creation. However, existing 3D style transfer methods primarily focus on transferring abstract artistic styles to 3D scenes. These methods often overlook the geometric information of the scene, which makes it challenging to achieve high-quality 3D texture transfer results. In this paper, we present GT 2 -GS, a geometryaware texture transfer framework for gaussian splatting. First, we propose a geometry-aware texture transfer loss that enables view-consistent texture transfer by leveraging prior view-dependent feature information and texture features augmented with additional geometric parameters. Moreover, an adaptive fine-grained control module is proposed to address the degradation of scene information caused by lowgranularity texture features. Finally, a geometry preservation branch is introduced. This branch refines the geometric parameters using additionally bound Gaussian color priors, thereby decoupling the optimization objectives of appearance and geometry. Extensive experiments demonstrate the effectiveness and controllability of our method. Through geometric awareness, our approach achieves texture transfer results that better align with human visual perception. Our homepage is available at https://vpx-ecnu.github.io/GT2-GS-website .
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Builds on17
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh et al.ICML 2021 · 47,906 citations
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 5,687 citations
- StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual LearningYihua Huang, Yue He, Yu-Jie Yuan, Yu-Kun Lai et al.CVPR 2022 · 145 citations
- SNeRF: stylized neural implicit representations for 3D scenesThu Nguyen-Phuoc, Feng Liu, Lei XiaoSIGGRAPH 2022 · 99 citations
- Learning to Stylize Novel ViewsHsin-Ping Huang, Hung-Yu Tseng, Saurabh Saini, Maneesh Singh et al.ICCV 2021 · 98 citations
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