<i>đ˘</i>âStyle: Stylized Gaussian Splatting
Abstract We introduce đ˘âStyle, a novel algorithm designed to transfer the style of an image onto a 3D scene represented using Gaussian Splatting. Gaussian Splatting is a powerful 3D representation for novel view synthesis, asâcompared to other approaches based on Neural Radiance Fieldsâit provides fast scene renderings and user control over the scene. Recent preâprints have demonstrated that the style of Gaussian Splatting scenes can be modified using an image exemplar. However, since the scene geometry remains fixed during the stylization process, current solutions fall short of producing satisfactory results. Our algorithm aims to address these limitations by following a threeâstep process: In a preâprocessing step, we remove undesirable Gaussians with large projection areas or highly elongated shapes. Subsequently, we combine several losses carefully designed to preserve different scales of the style in the image, while maintaining as much as possible the integrity of the original scene content. During the stylization process and following the original design of Gaussian Splatting, we split Gaussians where additional detail is necessary within our scene by tracking the gradient of the stylized color. Our experiments demonstrate that đ˘âStyle generates highâquality stylizations within just a few minutes, outperforming existing methods both qualitatively and quantitatively.
Authors
- Renata G. Raidou
- Ă. KovĂĄcs (ORCID: https://orcid.org/0000-0002-0849-9032)
- Pedro Hermosilla (ORCID: https://orcid.org/0000-0003-3586-4741)
Institutions
- TU Wien (AT)
Publication Details
- Journal
- Computer Graphics Forum
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1111/cgf.15259
- Citations
- 6
- Primary Topic
- Computer Graphics and Visualization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 3.79