MVDream: Multi-view Diffusion for 3D Generation
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866909173074100224 |
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| author | Shi, Yichun Wang, Peng Ye, Jianglong Long, Mai Li, Kejie Yang, Xiao |
| author_facet | Shi, Yichun Wang, Peng Ye, Jianglong Long, Mai Li, Kejie Yang, Xiao |
| contents | We introduce MVDream, a diffusion model that is able to generate consistent multi-view images from a given text prompt. Learning from both 2D and 3D data, a multi-view diffusion model can achieve the generalizability of 2D diffusion models and the consistency of 3D renderings. We demonstrate that such a multi-view diffusion model is implicitly a generalizable 3D prior agnostic to 3D representations. It can be applied to 3D generation via Score Distillation Sampling, significantly enhancing the consistency and stability of existing 2D-lifting methods. It can also learn new concepts from a few 2D examples, akin to DreamBooth, but for 3D generation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_16512 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | MVDream: Multi-view Diffusion for 3D Generation Shi, Yichun Wang, Peng Ye, Jianglong Long, Mai Li, Kejie Yang, Xiao Computer Vision and Pattern Recognition We introduce MVDream, a diffusion model that is able to generate consistent multi-view images from a given text prompt. Learning from both 2D and 3D data, a multi-view diffusion model can achieve the generalizability of 2D diffusion models and the consistency of 3D renderings. We demonstrate that such a multi-view diffusion model is implicitly a generalizable 3D prior agnostic to 3D representations. It can be applied to 3D generation via Score Distillation Sampling, significantly enhancing the consistency and stability of existing 2D-lifting methods. It can also learn new concepts from a few 2D examples, akin to DreamBooth, but for 3D generation. |
| title | MVDream: Multi-view Diffusion for 3D Generation |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2308.16512 |