CAT3D: Create Anything in 3D with Multi-View Diffusion Models
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910449887346688 |
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| author | Gao, Ruiqi Holynski, Aleksander Henzler, Philipp Brussee, Arthur Martin-Brualla, Ricardo Srinivasan, Pratul Barron, Jonathan T. Poole, Ben |
| author_facet | Gao, Ruiqi Holynski, Aleksander Henzler, Philipp Brussee, Arthur Martin-Brualla, Ricardo Srinivasan, Pratul Barron, Jonathan T. Poole, Ben |
| contents | Advances in 3D reconstruction have enabled high-quality 3D capture, but require a user to collect hundreds to thousands of images to create a 3D scene. We present CAT3D, a method for creating anything in 3D by simulating this real-world capture process with a multi-view diffusion model. Given any number of input images and a set of target novel viewpoints, our model generates highly consistent novel views of a scene. These generated views can be used as input to robust 3D reconstruction techniques to produce 3D representations that can be rendered from any viewpoint in real-time. CAT3D can create entire 3D scenes in as little as one minute, and outperforms existing methods for single image and few-view 3D scene creation. See our project page for results and interactive demos at https://cat3d.github.io . |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_10314 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | CAT3D: Create Anything in 3D with Multi-View Diffusion Models Gao, Ruiqi Holynski, Aleksander Henzler, Philipp Brussee, Arthur Martin-Brualla, Ricardo Srinivasan, Pratul Barron, Jonathan T. Poole, Ben Computer Vision and Pattern Recognition Advances in 3D reconstruction have enabled high-quality 3D capture, but require a user to collect hundreds to thousands of images to create a 3D scene. We present CAT3D, a method for creating anything in 3D by simulating this real-world capture process with a multi-view diffusion model. Given any number of input images and a set of target novel viewpoints, our model generates highly consistent novel views of a scene. These generated views can be used as input to robust 3D reconstruction techniques to produce 3D representations that can be rendered from any viewpoint in real-time. CAT3D can create entire 3D scenes in as little as one minute, and outperforms existing methods for single image and few-view 3D scene creation. See our project page for results and interactive demos at https://cat3d.github.io . |
| title | CAT3D: Create Anything in 3D with Multi-View Diffusion Models |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2405.10314 |