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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2511.18441 |
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| _version_ | 1866911283213762560 |
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| author | Rutayisire, Lorenzo Capodieci, Nicola Pellacini, Fabio |
| author_facet | Rutayisire, Lorenzo Capodieci, Nicola Pellacini, Fabio |
| contents | Gaussian Splatting has emerged as a leading method for novel view synthesis, offering superior training efficiency and real-time inference compared to NeRF approaches, while still delivering high-quality reconstructions. Beyond view synthesis, this 3D representation has also been explored for editing tasks. Many existing methods leverage 2D diffusion models to generate multi-view datasets for training, but they often suffer from limitations such as view inconsistencies, lack of fine-grained control, and high computational demand. In this work, we focus specifically on the editing task of recoloring. We introduce a user-friendly pipeline that enables precise selection and recoloring of regions within a pre-trained Gaussian Splatting scene. To demonstrate the real-time performance of our method, we also present an interactive tool that allows users to experiment with the pipeline in practice. Code is available at https://github.com/loryruta/recogs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_18441 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ReCoGS: Real-time ReColoring for Gaussian Splatting scenes Rutayisire, Lorenzo Capodieci, Nicola Pellacini, Fabio Computer Vision and Pattern Recognition Graphics I.3.4 Gaussian Splatting has emerged as a leading method for novel view synthesis, offering superior training efficiency and real-time inference compared to NeRF approaches, while still delivering high-quality reconstructions. Beyond view synthesis, this 3D representation has also been explored for editing tasks. Many existing methods leverage 2D diffusion models to generate multi-view datasets for training, but they often suffer from limitations such as view inconsistencies, lack of fine-grained control, and high computational demand. In this work, we focus specifically on the editing task of recoloring. We introduce a user-friendly pipeline that enables precise selection and recoloring of regions within a pre-trained Gaussian Splatting scene. To demonstrate the real-time performance of our method, we also present an interactive tool that allows users to experiment with the pipeline in practice. Code is available at https://github.com/loryruta/recogs. |
| title | ReCoGS: Real-time ReColoring for Gaussian Splatting scenes |
| topic | Computer Vision and Pattern Recognition Graphics I.3.4 |
| url | https://arxiv.org/abs/2511.18441 |