Gaussian Splashing: Unified Particles for Versatile Motion Synthesis and Rendering
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866914882135261184 |
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| author | Feng, Yutao Feng, Xiang Shang, Yintong Jiang, Ying Yu, Chang Zong, Zeshun Shao, Tianjia Wu, Hongzhi Zhou, Kun Jiang, Chenfanfu Yang, Yin |
| author_facet | Feng, Yutao Feng, Xiang Shang, Yintong Jiang, Ying Yu, Chang Zong, Zeshun Shao, Tianjia Wu, Hongzhi Zhou, Kun Jiang, Chenfanfu Yang, Yin |
| contents | We demonstrate the feasibility of integrating physics-based animations of solids and fluids with 3D Gaussian Splatting (3DGS) to create novel effects in virtual scenes reconstructed using 3DGS. Leveraging the coherence of the Gaussian Splatting and Position-Based Dynamics (PBD) in the underlying representation, we manage rendering, view synthesis, and the dynamics of solids and fluids in a cohesive manner. Similar to GaussianShader, we enhance each Gaussian kernel with an added normal, aligning the kernel's orientation with the surface normal to refine the PBD simulation. This approach effectively eliminates spiky noises that arise from rotational deformation in solids. It also allows us to integrate physically based rendering to augment the dynamic surface reflections on fluids. Consequently, our framework is capable of realistically reproducing surface highlights on dynamic fluids and facilitating interactions between scene objects and fluids from new views. For more information, please visit our project page at \url{https://gaussiansplashing.github.io/}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_15318 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Gaussian Splashing: Unified Particles for Versatile Motion Synthesis and Rendering Feng, Yutao Feng, Xiang Shang, Yintong Jiang, Ying Yu, Chang Zong, Zeshun Shao, Tianjia Wu, Hongzhi Zhou, Kun Jiang, Chenfanfu Yang, Yin Graphics Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning We demonstrate the feasibility of integrating physics-based animations of solids and fluids with 3D Gaussian Splatting (3DGS) to create novel effects in virtual scenes reconstructed using 3DGS. Leveraging the coherence of the Gaussian Splatting and Position-Based Dynamics (PBD) in the underlying representation, we manage rendering, view synthesis, and the dynamics of solids and fluids in a cohesive manner. Similar to GaussianShader, we enhance each Gaussian kernel with an added normal, aligning the kernel's orientation with the surface normal to refine the PBD simulation. This approach effectively eliminates spiky noises that arise from rotational deformation in solids. It also allows us to integrate physically based rendering to augment the dynamic surface reflections on fluids. Consequently, our framework is capable of realistically reproducing surface highlights on dynamic fluids and facilitating interactions between scene objects and fluids from new views. For more information, please visit our project page at \url{https://gaussiansplashing.github.io/}. |
| title | Gaussian Splashing: Unified Particles for Versatile Motion Synthesis and Rendering |
| topic | Graphics Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2401.15318 |