Universal Beta Splatting
Fuente:
arXiv
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| Autores principales: | , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866915820771213312 |
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| author | Liu, Rong Gao, Zhongpai Planche, Benjamin Chen, Meida Nguyen, Van Nguyen Zheng, Meng Choudhuri, Anwesa Chen, Terrence Wang, Yue Feng, Andrew Wu, Ziyan |
| author_facet | Liu, Rong Gao, Zhongpai Planche, Benjamin Chen, Meida Nguyen, Van Nguyen Zheng, Meng Choudhuri, Anwesa Chen, Terrence Wang, Yue Feng, Andrew Wu, Ziyan |
| contents | We introduce Universal Beta Splatting (UBS), a unified framework that generalizes 3D Gaussian Splatting to N-dimensional anisotropic Beta kernels for explicit radiance field rendering. Unlike fixed Gaussian primitives, Beta kernels enable controllable dependency modeling across spatial, angular, and temporal dimensions within a single representation. Our unified approach captures complex light transport effects, handles anisotropic view-dependent appearance, and models scene dynamics without requiring auxiliary networks or specific color encodings. UBS maintains backward compatibility by approximating to Gaussian Splatting as a special case, guaranteeing plug-in usability and lower performance bounds. The learned Beta parameters naturally decompose scene properties into interpretable without explicit supervision: spatial (surface vs. texture), angular (diffuse vs. specular), and temporal (static vs. dynamic). Our CUDA-accelerated implementation achieves real-time rendering while consistently outperforming existing methods across static, view-dependent, and dynamic benchmarks, establishing Beta kernels as a scalable universal primitive for radiance field rendering. Our project website is available at https://rongliu-leo.github.io/universal-beta-splatting/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_03312 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Universal Beta Splatting Liu, Rong Gao, Zhongpai Planche, Benjamin Chen, Meida Nguyen, Van Nguyen Zheng, Meng Choudhuri, Anwesa Chen, Terrence Wang, Yue Feng, Andrew Wu, Ziyan Graphics Computer Vision and Pattern Recognition Image and Video Processing We introduce Universal Beta Splatting (UBS), a unified framework that generalizes 3D Gaussian Splatting to N-dimensional anisotropic Beta kernels for explicit radiance field rendering. Unlike fixed Gaussian primitives, Beta kernels enable controllable dependency modeling across spatial, angular, and temporal dimensions within a single representation. Our unified approach captures complex light transport effects, handles anisotropic view-dependent appearance, and models scene dynamics without requiring auxiliary networks or specific color encodings. UBS maintains backward compatibility by approximating to Gaussian Splatting as a special case, guaranteeing plug-in usability and lower performance bounds. The learned Beta parameters naturally decompose scene properties into interpretable without explicit supervision: spatial (surface vs. texture), angular (diffuse vs. specular), and temporal (static vs. dynamic). Our CUDA-accelerated implementation achieves real-time rendering while consistently outperforming existing methods across static, view-dependent, and dynamic benchmarks, establishing Beta kernels as a scalable universal primitive for radiance field rendering. Our project website is available at https://rongliu-leo.github.io/universal-beta-splatting/. |
| title | Universal Beta Splatting |
| topic | Graphics Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2510.03312 |